WWAR Vol.2.019

•
•
•
•
•
•
•
•
•
•
•

M
India Equity Strategy
FOUNDATION
Growth Under Any Government
Indicators suggest the May election results are too close to call. That said, if we
are right about India's growth cycle, the ballot may fade in importance for the
equity market as 2019 unfolds.
About 930 million voters will be eligible to cast votes three months
from now in the world's biggest ever democratic election, whose
results are about four months away. The biggest investor concern
is a weak coalition government incapable of making quick administrative
decisions, inducing political uncertainty and a sharp market
correction.
India is arguably at the start of a new multi-year growth cycle, especially
in terms of corporate profits. This, in our view, blunts the
potential impact of the election results. Hence, we make an out-ofconsensus
call that there is a 75% chance the election season will
not result in outsized market moves as seen in 2004 and 2009.
We are watching pre-poll alliances and growth to judge how the
election results may pan out. We lay down four possible scenarios
for government formation with only one scenario where India votes
in a fragmented coalition government with the potential to derail
share prices. This is because the market currently appears agnostic
to elections based on how we read trailing performance, valuations
and correlations.
Nevertheless, those worried about a tail risk unfolding – and tail
risks are not priced into stocks, in our view – should barbell their
portfolios. Volatility or price oscillations could rise in the next four
months, but with India likely on the cusp of a new multi-year growth
cycle, such volatility may not be worth trading unless one is
extremely short-term oriented. As the market negotiates the elections
over the next four months, it is also possible that growth
stocks will be more volatile than pure defensive names. Based on
our view that the elections' impact on share prices will likely be
muted, the time to buy growth at a reasonable price (GARP) is now.
Hence, we are positioned for a cyclical upturn with overweights in
banks, consumer discretionary and industrials.

M
Executive Summary: Behave As Though
There Are No Elections
FOUNDATION
Results too close to call at this stage: We believe the elections
essentially hinge on two things: economic growth and pre-poll alliances.
At this moment the economy is neither too hot nor too cold,
nor are the pre-poll alliances going in any one direction. We therefore
think the 2019 election outcome is currently too close to call.
Price volatility could head higher: Given our view that the election
outcome is getting tighter, volatility in share prices could rise. The
Sensex averages about a 50% move from trough to top in any
12-month period going back 25 years, whereas it has moved only 27%
since the current government assumed office. Volatility means more
oscillations in share prices rather than a directional move in the
market either up or down.
What is priced in? It is unlikely that the market is as optimistic as it
has been in the past going into the 2019 general elections given that
we already have a majority government in office and hence the
country may have to contend with the prospect of a weaker government
at the center. If the market lags history in the run-up to the
polls, as we expect it to, it may ultimately be less vulnerable to an
unfavorable election outcome (one that does not bring in a majority
government). Our correlation work, along with trailing prices and
valuations, shows that stocks are currently agnostic to the elections.
Election impact may turn out to be less than the consensus currently
thinks: Unless we get a scenario of a weak coalition with a
lead party only in a supporting role (25% probability, in our view),
leaving the country vulnerable to a quick follow-up poll, we think
Exhibit 1:
One-month VAR: Little tail risk in price action
-28%
-24%
-20%
-16%
-12%
99%/One-month VaR for BSE Sensex
Historically when VaR hits 12% VaR,
tail risks seemed to be in play
that market performance will eventually focus on a likely new
growth cycle rather than the election outcome, beyond some heightened
volatility. This view changes if the market, over the next three
months, starts pricing in a strong government.
Tail risk is not in the price, so be warned: Historical value-at-risk
( Exhibit 1 ) tells us how much tail risk could be in the price. Given how
low this number is, one thing seems certain: the market is not concerned
about tail risk. This is something to be aware of.
How should the equity market assess the new government? The
new government needs to be assessed for its execution on things
such as infrastructure and ease of doing business and its approach to
fiscal management and the inflation dynamic. However, whatever
the government does may not affect the markets in 2019 or even
2020. History supports this view. If a new government takes an easier
stance on the fiscal deficit and on inflation, it could cause the structural
decline in share price volatility to reverse as well as adversely
affect domestic flows into equities.
Barbell portfolio for those who worry; the rest should focus on
the new multi-year growth cycle: We think investors should barbell
their portfolios in the run-up to the elections, if the elections are
worrying them. That said, our own recommended sector model portfolio
is biased for a cyclical recovery and a multi-year growth cycle
because we think that once the elections are out of the way, the
market will start focusing on India's emerging growth cycle.
Volatility or price oscillations could rise in the next four months, but
as we argue, with India likely on the cusp of a new multi-year growth
cycle, such volatility may not be worth trading unless one is
extremely short-term oriented. And while the market negotiates the
elections over the next four months, it is also possible that growth
stocks will be more volatile than pure defensive names. Based on our
view that the elections' impact on share prices is likely to be muted,
the time to buy growth at a reasonable price is now.
-8%
-4%
0%
1981
1983
1985
1987
1989
1991
1993
1995
1997
Source: Bloomberg, Morgan Stanley Research
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
We like GARP stocks among Banks, Discretionary Consumption and
Industrials – both large and mid-caps. We are underweight Consumer
Staples, Technology, Healthcare, Materials, and Utilities. We are neutral
on Energy and Telecoms ( Exhibit 2 & Exhibit 3 ).
MORGAN STANLEY RESEARCH 5

M
FOUNDATION
Exhibit 2:
Sector model portfolio
Performance relative to MSCI India
Sector OW/ UW (bps) MTD YTD 12M
MSCI India 1% 1% -2%
Consumer Disc. 500 -5% -5% -24%
Consumer Staples -300 -3% -3% 18%
Energy 0 6% 6% 14%
Financials 500 1% 1% 2%
Healthcare -200 -3% -3% -9%
Industrials 400 -7% -7% -5%
Technology -600 5% 5% 22%
Materials -100 -4% -4% -15%
Comm Services 0 -4% -4% -41%
Utilities -200 -6% -6% -11%
Source: RIMES, MSCI, Morgan Stanley Research. Past performance is no guarantee of future results.
Exhibit 3:
Focus list
Sector
Rating
Price as on
Jan 21, 2019
MCap ($
bn)
Avg 3M T/O
($ mn)
Rel to MSCI India
YTD Perf
12m Perf
2Y Fwd EPS
Growth
Bajaj Auto Cons. Disc. EW 2,685 10.9 16 -2% -14% 8%
M&M Cons. Disc. OW 730 12.2 38 -10% -2% 21%
Titan Cons. Disc. OW 963 12.0 36 3% 11% 26%
ITC Staples OW 290 49.9 41 2% 8% 14%
Reliance Industries Energy OW 1,238 107.8 146 10% 36% 22%
Bharat Financial Financials ++ 951 1.9 14 -7% -3% 110%
HDFC Bank Financials OW 2,148 82.1 92 0% 13% 22%
ICICI Bank Financials OW 372 33.6 105 2% 8% 45%
Indusind Bank Financials ++ 1,508 12.8 54 -6% -8% 25%
Shriram Transport Financials OW 1,115 3.6 21 -11% -20% 29%
ICICI Pru Life Financials OW 352 7.1 6 8% -16% 6%
SBI Financials OW 292 36.7 85 -2% -3%
Prestige Estates Financials OW 207 1.1 1 -6% -32% 6%
Apollo Hospitals Healthcare OW 1,326 2.6 12 5% 19% 92%
Ashok Leyland Industrials OW 91 3.7 34 -12% -23% 21%
Adani Ports Industrials OW 396 11.5 20 1% -6% 9%
Eicher Motors Industrials OW 20,028 7.7 36 -14% -27% 22%
L & T Industrials OW 1,315 25.9 44 -9% -2% 17%
Asian Paints Materials OW 1,422 19.2 30 3% 22% 16%
Ultratech Cement Materials EW 3,850 14.8 17 -4% -8% 22%
Source: RIMES, Morgan Stanley Research. ++ Ratings and price targets have been removed from consideration in this report because, under applicable law and/or Morgan Stanley policy, Morgan Stanley may be precluded
from issuing such information with respect to this company at this time. Past performance is no guarantee of future results. Transaction costs and dividends not included.
6

M
The Two Most Important Things To Watch
Pre-Elections
FOUNDATION
Predicting elections is not a fruitful task for three reasons. The first
is that outcomes are binary. The second is that it is always difficult to
tell what is in the price and hence hedging a particular outcome is
difficult. The third reason is that forecasting a range of outcomes is
of little utility because, unlike share price ranges, a range of political
outcomes is hard to express in portfolios. Understanding the drivers
of possible outcomes could still be useful in gaining some judgement
as to what could happen. Again, the futility of this is that the election
process is complex and simplifying drivers into individual factors is
prone to bias. Nevertheless, keeping all of the above in mind, very
simplistically speaking, we think that the 2019 elections will come
down to two things: economic growth and pre-poll alliances. At this
moment the economy is neither too hot nor too cold, nor are the prepoll
alliances going in any one direction. We therefore think the 2019
election outcome is currently too close to call.
Force of incumbency: The prevailing myth is that anti-incumbency
is a crucial factor in Indian elections and that the ruling party is always
at a disadvantage. However, our proprietary "Force of Incumbency
Index" (for details on the computation of this index please refer to
The World's Biggest Democratic Elections: How to Forecast Them &
What to Do with Portfolios) shows that election results are in large
part led by the nation's growth cycle, by about 15 months ( Exhibit
4 ). Accelerating GDP growth augurs well for incumbent governments,
whether at the central or state level. From a fundamental
standpoint, this is hardly surprising, since the electorate ultimately
seeks better living standards (transmitted via higher growth) from
the actions of its elected representatives. Since growth appears to
have come off the lows, we believe it is fair to say the force of anti-incumbency
is fading. At the same time, growth is not strong enough
for the incumbents to be complacent.
Pre-poll alliances: We think two states – Maharashtra and Uttar
Pradesh – are likely to be crucial to the results in 2019 ( Exhibit 3 ).
These two states are the largest contributors to the Lower House,
with 128 seats, or almost one-quarter of that chamber's total of 543
elected representatives. Currently, the BJP has 94 seats or a third of
its total count in the Lower House from these two states. Apart from
that, alliances in these states are prone to producing polarized
results when pre-poll alliances are formed because their electorates
are relatively fragmented.
In Uttar Pradesh, for example, it is about how the Samajwadi Party
and Bahujan Samajwadi Party align. Their pre-poll alliance
announced in early January is negative for the incumbent BJP-led
NDA, which holds over 70 seats in the Lower House from Uttar
Pradesh. In Maharashtra, Shiv Sena is a key player. Given what has
happened in Uttar Pradesh, the BJP could have a greater sense of
urgency to engage in a pre-poll alliance, for example with the Shiv
Sena. Bihar is a good guide in this regard where the BJP will contest
only 17 of 40 seats, giving more seats to its partners. The BJP currently
holds 22 seats in the Lok Sabha in Bihar so is already set for a
decline in the number of seats it can win in Bihar.
Exhibit 4:
Growth leads the election performance of incumbent governments
20
15
10
5
0
-5
-10
-15
-20
Force of incumbency index
GDP growth (lead of 15M) - RS
2003
2004
2004
2005
2006
2007
2007
2007
2008
2008
2008
2009
2009
2009
2011
2012
2012
2012
2013
2013
2014
2014
2014
2015
2016
2016
2017
2017
2018
2018
2018
Source: ECI website, CEIC, Morgan Stanley Research
12%
10%
8%
6%
4%
2%
0%
Exhibit 5:
Regional parties will hold the key in 2019
55%
50%
45%
40%
35%
30%
25%
20%
1984 1989 1991 1996 1998 1999 2004 2009 2014
Source: Election commission of India, Morgan Stanley
Votes won by parties
other than BJP and INC
Seats won by parties other
than the BJP and the INC
MORGAN STANLEY RESEARCH 7

M
FOUNDATION
Regional parties are important: Of the next four largest states in
terms of seat count, the two big national parties (INC and BJP) have
hardly any presence in three of them (Andhra Pradesh – now split
into two states, West Bengal, and Tamil Nadu). For example, in the
2014 general elections the two main parties won just 12 out of 123
seats in these three states. The rest of the seats went to "regional"
parties (technically speaking, the All India Trinamool among others
is a national party). It is also noteworthy that parties other than the
INC and BJP have won at least 40% of the seats in the past six elections
( Exhibit 2 ). Whichever way one looks at India's election
dynamics, pre-poll tie-ups are important to the ultimate outcome.
Exhibit 6:
States with the largest seats in the Lower House (Lok Sabha)
Lok Sabha Seats BJP INC BSP SP NCP JD(U) Shiv Sena Others Total
Uttar Pradesh 71 2 5 2 80
Maharashtra 23 2 4 18 1 48
Andhra Pradesh/Telangana 3 2 37 42
West Bengal 2 4 36 42
Bihar 22 2 1 2 13 40
Tamil Nadu 1 38 39
Madhya Pradesh 27 2 29
Karnataka 17 9 2 28
Gujarat 26 26
Rajasthan 25 25
Kerala 8 12 20
Orissa 1 20 21
Assam 7 3 4 14
Jharkhand 12 2 14
Punjab 2 3 8 13
Chhattisgarh 10 1 11
Haryana 7 1 2 10
Remaing 18 States/UT 26 5 10 41
Total 282 44 0 5 5 2 18 187 543
Source: Election Commission of India, Note: Seat count as at May 2014. For West Bengal others include 34 seats won for All India Trinamool Congress, likewise for Andhra Pradesh, 16 seats for Telugu Dessam Party, for
Orissa, 20 seats for Biju Janata Dal and for Tamil Nadu 35 seats for AIADMK
*Andhra Pradesh has been split into two states since 2014 – in the 2019 elections, Andhra Pradesh will send 25 representatives to the Lower House whereas Telangana, the new state that has been formed, will send 17.
8

M
FOUNDATION
Implication – More volatility in share
prices is possible
Exhibit 7:
Unusually low volatility since 2016 – Market set up for a wider range of
outcomes
180%
Sensex : Trailing 12M High minus Trailing 12M Low as % of the Low
160%
140%
120%
100%
80%
60%
Average = 50%
40%
20%
0%
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
Source: Morgan Stanley Research, Bloomberg
Given our view that the election outcome is getting tighter, volatility
in share prices could rise over the next four months ( Exhibit 8 ). It is
common belief that volatility in stock prices rises before the elections.
This belief is not wrong – but, that said, 1989 and 2014 were
exceptions to the rule. The exceptions contain a message. If volatility
falls in the run-up to the elections, it then tends to rise after the elections.
History suggests that stock price volatility will be higher in the
next four months (the time between now and the May elections). If
volatility does not rise before the elections, because the market
starts to price in a majority government, it will likely rise after the
elections.
Another point to note is that the range of annual market moves has
been relatively subdued versus history in recent quarters. The possible
events of 2019 probably set the market up for mean reversion
in Sensex moves. The Sensex averages about a 50% move from
trough to top in any 12-month period going back 25 years whereas it
has moved only 27% since the current government assumed office
( Exhibit 7 ). Volatility could rise in the next four months, but as we
argue later, with India likely on the cusp of a new multi-year growth
cycle, such volatility may not be worth trading unless one is
extremely short-term oriented. One more thing is that volatility
should be not conflated with a drawdown in the index, rather it
implies more oscillations.
Exhibit 8:
BSE Sensex volatility: Pre- and post-elections
Election Month/Year May-84 May-89 May-91 May-96 Mar-98 Oct-99 May-04 May-09 May-14 May-19
Avg 3M Volatility 12M to 6M prior to elections (a) 1.1% 3.1% 4.9% 2.6% 2.6% 4.4% 2.5% 4.5% 2.1% 1.7%
Avg 3M Volatility 6M prior to elections (b) 1.4% 2.5% 5.4% 4.0% 3.6% 4.4% 3.8% 6.3% 1.8% 2.3%
Change (b-a) 0.4% -0.6% 0.5% 1.4% 1.0% 0.0% 1.3% 1.9% -0.3% 0.6%
Avg 3M Volatility 6M post elections © 2.4% 3.8% 3.7% 2.8% 3.7% 3.8% 2.9% 4.4% 2.1%
Change (c-b) 0.9% 1.3% -1.7% -1.2% 0.1% -0.6% -0.9% -1.9% 0.4%
Source: RIMES., Morgan Stanley Research
MORGAN STANLEY RESEARCH 9

M
The Two Most Important Things To Watch
During The Elections
FOUNDATION
Given the history of 2004 and 2009, when the market produced significant
swings around election time, investors appear to be hyper-focused
on what the election results could do the market. So in this
regard we think there are two important things to monitor – how the
market behaves between now and May and what is priced in
regarding the outcome:
to elections. The relative performance too suffered and has been
more volatile than usual (possibly due to the volatility in crude oil
prices) but remains a tad ahead of the historical average relative performance
( Exhibit 11 ). If the market lags history in the run-up to the
polls, as we expect it to, it may be less likely to react to an unfavorable
election outcome (one that does not bring in a majority government).
Market in the run-up to elections: If the past five general elections
are a guide, the market's usual approach in the run-up to elections is
one of optimism ( Exhibit 9 ). However, the big change from the past
is that none of the elections since the mid-1990s has started with a
majority government at the helm of affairs in the run-up to the elections.
Put another way, the market could always enter past elections
with the hope of a stronger government than the incumbent. This
does not apply in 2019, as there is a possibility of a weaker government
(Scenario 2, 3, 4). Hence, going into the 2019 general elections,
it is unlikely that the market is as optimistic as it has been in the past.
What is priced in? We have used three approaches to judge what is
priced in to the market – trailing performance, current valuations vs.
history and how much macro is influencing share prices.
Trailing performance: Given the idiosyncratic event relating to the
non-banking finance sector, the market gave up a lot of performance
in October and thus its absolute performance ( Exhibit 10 ) is now
lagging behind the historical average performance four months prior
Valuations: Absolute valuations are in line with history, i.e., where
they have been approximately four months ahead of elections in the
past ( Exhibit 12 ). To that extent, the market is not pricing in anything
about the elections that is different from history. However, elections
are not the only factor influencing the market, so we have to view this
statement with caution.
Correlations of returns across stocks: While on an absolute basis
correlations of returns across stocks with the market have risen from
the low point they hit last year, suggesting a macro trade is in play,
correlations are still nowhere close to previous highs. Meanwhile,
relative to both EM and DM cohorts, correlations of stock returns to
the market are actually falling and lower than history ( Exhibit 13 ).
It means that Indian equities are not in full-blown macro trade mode
(as they appear to be in other markets, especially in the developed
world). This means that the Indian market is still agnostic to election
outcomes. If the market became more sensitive to likely election outcomes,
we would expect correlations to rise not fall.
Exhibit 9:
Market performance before and after elections
Election Cycle
6M pre election
Performance Sensex Abs perf MSCI India
3M pre election
Relative to
EM Sensex Abs perf MSCI India
Relative to
EM
Sensex
Abs perf
3M post election
MSCI India
Relative
to EM
Net Impact
Relative
Absolute to EM
1984 9% 2% 30% 33%
1989 1% -3% 69% 67%
1991 9% 7% 44% 51%
1996 20% 23% 20% 6% 7% 5% -5% -8% -4% 1% -1%
1998 -9% -14% -14% 7% 6% 6% -8% -12% -1% -1% -7%
1999 32% 35% 49% 9% 14% 26% 6% 15% -8% 16% 29%
2004 10% 8% 22% -10% -11% 1% -2% -3% -3% -12% -14%
2009 30% 31% 3% 26% 27% 0% 27% 32% 9% 54% 59%
2014 18% 23% 14% 18% 21% 12% 8% 6% 2% 27% 27%
Avg. 13% 18% 16% 7% 11% 8% 19% 5% -1% 26% 16%
Source: RIMES, MSCI, Morgan Stanley Research
10

M
FOUNDATION
Exhibit 10:
Absolute market performance lagging history (four months ahead of
elections)
150
140
130
120
110
100
Sensex Rebased to 12M prior
to elections
Avg. of the past 5
elections
Exhibit 11:
Relative performance a tad ahead of history but looking weak
125
120
115
110
105
100
MSCI India US$ Index Perf.
Relative to MSCI EM 12M
Pre & Post Elections
May 2019
Avg. of the past 5
elections
90
May 2019
95
80
-52
-48
-44
-40
-36
-32
-28
-24
-20
-16
-12
-8
-4
Source: RIMES, Morgan Stanley Research
8
12
16
20
24
28
32
36
40
44
48
52
0
4
90
-52
-48
-44
-40
-36
-32
-28
-24
-20
-16
-12
-8
-4
0
4
8
12
16
20
24
28
32
36
40
44
48
52
Source: RIMES, Morgan Stanley Research
Exhibit 12:
Valuations bang in line with historical position ahead of elections
7.0
MSCI India PB
1991-1996 1996-1998
1998-1999 1999-2004
2004-2009 2009-2014
6.0
2014-2019
5.0
4.0
3.0
2.0
1.0
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Source: RIMES, MSCI, Morgan Stanley Research
Exhibit 13:
Return correlations across stocks with the market depressed – no
macro trade in play
0%
-5%
-10%
-15%
-20%
-25%
-30%
-35%
-40%
-45%
-50%
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Source: RIMES, MSCI, Morgan Stanley Research
Gap between correlation of returns of MSCI India vs. MSCI DM
Gap between correlation of returns of MSCI India vs. MSCI EM
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
MORGAN STANLEY RESEARCH 11

M
FOUNDATION
Implications: Barbell portfolio for election
results and beyond
The way to tackle the run-up to elections is to prepare portfolios for
various scenarios. Such an approach does not guarantee outperformance
for any particular outcome, but is likely to protect portfolios
from extreme performance. Hedge funds have the option to buy
long-dated index options although large portfolios may not permit
this strategy. Of course, portfolio managers also have the option to
take a view on the likely election outcome and the ensuing market
reaction and tailor the portfolio to match the view: Hence, buy beta
and leverage if one believes in a better-than-expected election result
and vice versa – the challenge is to know what the market is pricing
in. Exhibit 14 outlines how portfolios should look in the different
possible scenarios. In scenario 1 the market continues to build on the
nascent growth signals for a full-blown profit cycle whereas in scenario
4 the market starts pricing in a deceleration in growth and so
the portfolio becomes defensive. In between these scenarios, the
portfolios gradually lose their cyclical nature and become defensive.
The average portfolio (average of the four scenarios) appears a tad
defensive, which is consistent with our view that the market enters
the 2019 polls with a majority government already at the helm and
hence has to contend with the prospect of a weaker government at
the center. That said, our own recommended sector model portfolio
is biased for a cyclical recovery because we think that once the elections
are out of the way, the market will start focusing on India's
emerging multi-year growth cycle.
Possible election outcomes
There is a wide range of potential outcomes because of
how Indian elections are conducted (first past the post).
A small change in vote share can lead to a big shift in seat
count. The margin of error is too large to allow a forecast
consisting of a narrow range of outcomes. We attach a
25% probability to each of these outcomes.
Scenario 1 – an absolute majority for one of the national
parties, which means winning around 260+ seats like the
BJP-led NDA in 2014.
Scenario 2 – 200-220 seats for one of the two major
national parties (INC or BJP), what we call a weak
majority government, like the INC-led UPA in 2009.
Scenario 3 – a coalition with the lead party winning 160-
180 seats. We saw such governments in 1998 and 1999.
Scenario 4 – a weak coalition with the participation of a
lead party only in a supporting role. Such support is from
the outside, leaving the government vulnerable. 1996 is a
good example of such an outcome.
Exhibit 14:
Our sector portfolio is different from the scenarios because elections are not the only thing the market is dealing with
Sensex path for the
coming 12 months
Scenario 1: Bull Case -
Buy domestic cyclicals
and rate sensitives
Lead party with circa 260+
seats
Scenario 2: Buy
consumption, global
stocks
Lead party with 200-220
seats
Our bull case of 47000 Our base case of 42000
Scenario 3: Go closer to
the benchmark, avoid
high beta and cyclicals
Lead party with 160-180
seats in a coaltion
Scenario 4: Get defensive
Weak coalition with only
supporting role by lead party
Somewhere between base
Our bear case of 33000
and bear case
Average of four
scenarios
Our Current
Sector
Positions
Consumer Disc OW OW EW UW OW OW
Consumer Staples UW UW OW OW EW UW
Energy OW EW EW UW EW EW
Financials OW OW EW UW OW OW
Healthcare UW UW UW OW UW UW
Industrials OW OW UW UW EW OW
Info Tech UW UW EW OW UW UW
Materials OW OW EW UW OW UW
Communication Services UW EW EW OW EW EW
Utilities UW UW OW OW EW UW
Source: Morgan Stanley Research
12

M
The Two Most Important Things To Watch
Post Elections
FOUNDATION
Exhibit 15:
Execution on road infrastructure: Pace of execution could change post
elections
35
30
25
20
15
10
5
0
6.5
F2007
Roads constructed (NHAI +
ministry)
10.1
F2008
12.3
F2009
13.7
F2010
10.8
F2011
13.7
F2012
15.7
F2013
Source: PIB, NHAI, Ministry of Roads, Morgan Stanley Research
11.6 11.9
F2014
Kms/day
Investors attribute importance to government formation because
they believe that stronger governments can drive favorable legislation
(for growth) and also take quicker decisions with a concomitant
impact on economic growth. On the first point we think that legislation
in India is a consensus process. Even though the NDA has had an
absolute majority in the Lower House, its minority position in the
Upper House has meant that legislation was only possible via consensus
over the past four and half years. Irrespective of the general
election outcome, we do not see this changing. The BJP will increase
its seat count in the Upper House thanks to the numerous state election
wins in the past four years but will likely remain short of the
halfway mark. So even if it came back to office, passing legislation will
remain a consensus process. The laws that come to the Parliament
for passage can still be a function of the ideology of the party (or
parties) running the government. However, because lawmaking is a
consensus process, extreme positions are quite unlikely unless the
general polity is in agreement.
Pace of execution: The second point on the ability to take quicker
decisions is not linked to the strength of the government but is more
dependent on the individuals running the government. If there is a
change in government in May, investors should keenly watch the
F2015
16.5
F2016
22.6
F2017
26.9
F2018
32.0
F2019e
pace of execution to get cues about medium-term growth. In the
meanwhile, the work done over the past few years by the present
government will continue to influence growth over the next three to
four years, and a change in government is unlikely to meaningfully
change our view that India is entering a new growth cycle (see the last
section of this report).
Theoretically, a minority government brings the prospect of slower
execution, which leads to higher growth volatility. The lowest volatility
in growth has been for the most recent period of four years,
which also featured India's strongest government in over three decades.
However, the level of growth appears to be affected by other
factors too, as well as the starting point. A weak government does
not necessarily equate to poor growth and vice versa. The economic
environment is a function of policy choices. As we have seen in the
past, these policies are difficult to predict based purely on the nature
of the government in power.
Fiscal and inflation dynamic: The rhetoric is that a minority government
could be susceptible to lifting social spending; combined with
lower fiscal discipline, the outcome could be higher inflation.
However, data do not support this outcome; rather, they defend a
view that the predictability of inflation declines with weaker governments
( Exhibit 16 , Exhibit 17 , Exhibit 16 ). All this said, none of this
factors into our forecasted outcomes. At best these represent risks
of a fragmented coalition government (one in four chance based on
our scenario analysis). However, we will still watch how a new government
handles the fiscal deficit and, consequently, how India's
inflation dynamic unfolds. The reason is that the present government
has structurally altered India's inflation trajectory by a combination
of good fiscal management, active intervention in food markets and
by setting a real rate agenda and headline CPI target for the RBI. To
us, this shift in the inflation dynamic has an important role to play in
long-term interest rates (lower for longer), the stock market multiple
(higher for longer), lower volatility of share prices and domestic
equity flows (which we believe are in a structural uptrend).
MORGAN STANLEY RESEARCH 13

M
FOUNDATION
Exhibit 16:
CPI and GDP growth – do governments matter?
1991-1996 1996-1998 1998-1999 1999-2004 2004-2009 2009-2014 2014-2019
Government Weak Majority Weak Coalition Weak Coalition Strong Coalition Strong Coalition Weak Majority Majority
CPI Inflation
YoY%
Average 10.1% 8.1% 8.7% 3.9% 6.1% 10.1% 4.6%
Stdev 2.7% 2.2% 6.1% 1.0% 2.1% 2.0% 1.3%
Z-score 0.27 0.27 0.71 0.25 0.33 0.20 0.28
Real GDP
Growth YoY%
Source: RBI, CSO, Morgan Stanley Research
Average 5.0% 6.0% 5.6% 5.6% 8.1% 7.4% 7.4%
Stdev 1.8% 1.8% 1.2% 2.3% 2.6% 2.2% 0.8%
Z-score 0.36 0.30 0.22 0.41 0.32 0.30 0.11
Exhibit 17:
CPI inflation over the past seven governments
Exhibit 18:
Real GDP growth over the past seven governments
25.0%
20.0%
15.0%
CPI Inflation YoY% 1991-1996
1996-1998
1998-1999
1999-2004
2004-2009
2009-2014
2014-2018
14.0%
12.0%
10.0%
8.0%
1991-1996
1996-1998
1998-1999
1999-2004
2004-2009
2009-2014
2014-2018
Real GDP Growth YoY%
10.0%
6.0%
5.0%
4.0%
0.0%
2.0%
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
0.0%
Source: RBI, Morgan Stanley Research
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Source: CSO, Morgan Stanley Research
14

M
FOUNDATION
Implications: Market may not react
significantly to election outcomes
In the past seven elections, spread over 27 years, India has had only
one majority government – the latest one, which was elected in 2014.
The weakest coalition governments were formed in 1996 (United
Front) and 1998 (led by the BJP) and lasted for only two years and one
year respectively. Real GDP growth has averaged 6.8% p.a. from
F1993 to F2019 with the best fiscal year being F2011 and the worst
being F2009. The market (MSCI India) has risen over 6.5x in USD
terms from F1993 to F2019 vs. the ACVI index rising 3.6x and EM
rising 3x. The BSE Sensex is up 15.9x during this period.
Does a minority government hurt stocks? The bottom line here is
that the strength of governments (or lack thereof) appears to have
mattered little to market performance beyond the immediate term.
Eventually the share prices respond to growth and inflation, which
again appear to be a function of policy choices (as listed above) and
global factors rather than the strength of the government. Unless we
get a Scenario 4 (a weak coalition), we think market performance will
eventually focus on a likely new multi-year growth cycle rather than
the election outcome beyond some heightened volatility. Of course,
this view changes if the market in the next four months starts pricing
in a strong government. 2004 and 2009 are contrasting examples of
how volatile the market can be. Also, despite poor outcomes in 1996
and 1998, there was hardly any move in stocks immediately after
elections ( Exhibit 19 & Exhibit 20 ). Beyond 2019 and possibly even
2020, the actions of the new government around fiscal policy, inflation
dynamics and pace of execution could become more relevant to
the market and the economy.
Exhibit 19:
What happens to stocks immediately after elections depends on what
has been priced in
Day May-96 Mar-98 Oct-99 May-04 May-09 May-14
-3 -1% -3% 1% -5% -2% 0%
-2 3% 2% -1% 0% -1% 1%
-1 -1% 0% -2% 1% 3% 1%
0
Day 0 is the election result day
1 1% 3% -1% -7% 22% 2%
2 2% -1% 2% -11% -1% 0%
3 0% -1% 0% 9% 0% 0%
Who ran
the Govt
United
Front NDA NDA UPA UPA NDA
Nature of
govt
Weak
coalition
Weak
coalition
Source: RIMES, MSCI, Morgan Stanley Research
Strong
coalition
Strong
coalition
Weak
Majority
Majority
Exhibit 20:
Strength of the government or lack thereof does not seem to matter to
markets beyond the near term
Start of term date 1999 2004 2009 2014
Year 1 -9% 24% 59% 6%
Year 2 -35% 82% 6% -11%
Year 3 7% 23% -27% 21%
Year 4 56% 21% 20% 8%
Year 5 (3M before end of term) 33% -54% -10% -6%
Abs performance during the term 76% 65% 76% 86%
Rel performance 1999 2004 2009 2014
Year 1 -6% -4% 17% 4%
Year 2 0% 14% -11% 17%
Year 3 -1% 6% -13% -4%
Year 4 9% 0% 9% -6%
Year 5 (3M before end of term) 10% 0% -1% 8%
Term performance (relative) 10% 16% -2% 18%
Source: RIMES, MSCI, Morgan Stanley Research.
MORGAN STANLEY RESEARCH 15

M
India Is Likely Entering A Multi-year Growth
Cycle
FOUNDATION
Exhibit 21:
Investment as % of GDP
45%
Investment(% of GDP)
40%
35%
30%
25%
20%
15%
10%
Linear (Investment(% of GDP))
Growth appears to have troughed, led by benign inflation, a turn in
government capex, recovery in consumption and exports, and the
passage of one-time shocks like GST and demonetization. The investment
rate has now gone well below trend – reminiscent of 2002-03.
With counter-cyclical government capex already in place, capacity
utilization and asset turn above average, and growth likely
improving, a private capex cycle is in the offing post elections
( Exhibit 21 ). We believe this sets the stage for an improvement in
corporate profit margins.
5%
F1952
F1955
F1958
F1961
F1964
F1967
F1970
F1973
F1976
F1979
F1982
F1985
F1988
F1991
F1994
F1997
F2000
F2003
F2006
F2009
F2012
F2015
F2018
Source: CEIC, Morgan Stanley Research
Our 2019 outlook note is inspired by Howard Mark's latest book
'Mastering the Market Cycle'. As Howard Mark says, where we are in
the cycle contains significant information about where we could be
heading. So where exactly are we in the cycle as far Indian stocks are
concerned? The political cycle (measured as policy certainty) is likely
to turn down, growth is likely moving higher, credit growth seems to
be at the beginning of a new cycle, terms of trade are improving, rates
are probably taking a brief pause before continuing to head higher,
and profit margins appear to be at the start of a new upcycle. Finally,
valuations are bang in the middle of the historical range and could go
either way depending on other factors, but we opine that they are not
pricing in a multi-year growth cycle.
As a consequence, credit growth, which put in a bottom last year,
seems to be entering a new cycle ( Exhibit 23 ). Indeed, the peak of
the previous cycle was way above history and thus the recent trough
was well below history. Revenue growth for Corporate India has been
accelerating for the past several quarters and is now at a five-year
high ( Exhibit 24 ). Revenue growth could be heading higher in 2019.
The share of profits in GDP or profit margin seem to be putting in a
trough and could be entering a new medium-term cycle, which could
last for five years and result in strong profit growth ( Exhibit 25 ). As
with profit margins, ROEs seem to be putting in a bottom and preparing
for a new upcycle ( Exhibit 26 ). Asset turn has already risen.
Index target: Our Dec-19 Sensex target is 42,000, implying upside
of 15% and 20% in INR and USD terms, respectively, compared with
our MSCI EM index USD upside of 7%.
Indeed, we thought the growth cycle would turn a couple of years
ago, but our view proved incorrect mainly due to two major shocks
to the economy arising from demonetization and the implementation
of GST. With these now absorbed and with the policy work on
infrastructure and inflation, the growth trough may be behind us.
This increases our confidence that we may be in a new growth cycle,
albeit this is about probabilities rather than certainty, i.e., just given
where we are in long-run cycles, the likelihood is greater that we turn
up rather than down
16

M
FOUNDATION
Exhibit 22:
Morgan Stanley forecasts at a glance
F2017 F2018E F2019E F2020E
GDP Growth (new) 7.1% 6.7% 7.6% 7.6%
IIP Growth 4.6% 4.4% 4.9% 5.2%
Average CPI 4.5% 3.6% 3.9% 4.3%
Repo Rate (year end) 6.25% 6.00% 6.50.% 7.25%
CAD% of GDP -0.7% -1.9% -2.5% -2.3%
Sensex EPS 1443 1479 1789 2210
Sensex PE 24.2 23.6 19.5 15.8
EPS growth YoY 2.3% 2.5% 21.0% 23.5%
Broad Market Earnings Growth 0.0% 3.0% 20.0% 22.0%
Broad Market PE 28.7 27.9 23.2 19.1
Source: RIMES, MSCI, Morgan Stanley Research (E) estimates
Exhibit 23:
Trailing 3-year bank credit growth
36%
Trailing 3-yr Credit Growth
32%
28%
Exhibit 24:
Broad market revenue growth
30%
Revenue growth (Broad Market -
1178 cos) RS
24%
20%
16%
10%
12%
8%
-10%
4%
Oct-91
Oct-93
Oct-95
Oct-97
Oct-99
Oct-01
Oct-03
Oct-05
Oct-07
Oct-09
Oct-11
Oct-13
Oct-15
Oct-17
Sep-04
Sep-05
Sep-06
Sep-07
Sep-08
Sep-09
Sep-10
Sep-11
Sep-12
Source: Capitaline, company data, Morgan Stanley Research
Sep-13
Sep-14
Sep-15
Sep-16
Sep-17
Sep-18
Source: RBI, Morgan Stanley Research
Exhibit 25:
Exhibit 26:
India's corporate profits to GDP
India's ROE trend
8%
7%
6%
5%
Corporate Profits to GDP
24%
22%
20%
ROE Trend
4%
18%
3%
2%
1%
16%
14%
0%
12%
F1992
F1993
F1994
F1995
F1996
F1997
F1998
F1999
F2000
F2001
F2002
F2003
F2004
F2005
F2006
F2007
F2008
F2009
F2010
F2011
F2012
F2013
F2014
F2015
F2016
F2017E
Source: CMIE, Morgan Stanley Research (E) estimates
10%
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Source: Worldscope, RIMES, Morgan Stanley Research
MORGAN STANLEY RESEARCH 17

January 22, 2019 07:15 AM GMT
India Economics – Macro Indicators Chartbook | Asia
Pacific
Macro Stability Improves,
Growth Softens
Macro stability improved on the back of lower oil prices.
Growth indicators softened in 4Q18.
MORGAN STANLEY INDIA COMPANY PRIVATE LIMITED
Upasana Chachra
ECONOMIST
Upasana.Chachra@morganstanley.com
+91 22 6118-2246
About this publication: The India Economics Macro
Indicators Chartbook is a monthly publication that
presents all the key macro indicators for the Indian
economy, which we believe provide a
comprehensive macro health check. This chartbook
summarizes the trends in key indicators for growth,
the external sector, inflation, monetary conditions,
and public finance.
Growth – trend softened: Domestic demand softened, with decline in auto sales,
weaker than expected industrial production and modest dip in PMI's. While
passenger vehicle sales declined at a slower pace in December, two wheeler and
CV sales declined at a faster pace. On the positive side, credit growth remains
robust tracking at 14.5% in January. External demand was lacklustre, with export
growth decelerating despite a weak base.
Price Stability - CPI and WPI decelerated in December: CPI inflation was largely
in line with expectations at 2.2% in December, however divergence between
headline and core CPI persisted with core CPI rising to 5.5% on the back of higher
health / education costs. WPI inflation decelerated more than expected,
reflecting weaker food and fuel inflation.
External Stability - Trade deficit narrowed more than expected: Trade deficit
narrowed to US$13.1bn (5.9% of GDP annualized) in Dec from US$16.7bn (7.5% of
GDP) in Nov, driven by broad-based weakness in imports. Given the slowdown in
imports across segments, trade deficit ex oil and ex oil / gold narrowed in Dec.
Financial Stability - Credit deposit remains elevated, RBI's OMO operations
continue to support liquidity: Credit-deposit ratio remains elevated at 77.6% in
Jan, a tad lower than 78.6% as of Dec end. This reflects continued wedge
between credit and deposit growth. At the margin, liquidity conditions improved
in Jan, with interbank liquidity deficit reducing to US$2.9bn in Jan (month to date)
vs. US$15bn in Dec. We believe that moderation in capital outflows and
continued support from RBI's OMO operation are helping liquidity conditions at
the margin. On a FYTD basis, RBI has made OMO purchases of INR 2260bn
(including planned purchase for Jan).
Central government fiscal balances improved a tad in Nov: Headline fiscal deficit
declined in Nov on a YoY basis led by contraction in expenditure and some
pickup in receipts. The fiscal deficit (on 12M trailing sum) narrowed to 3.8% of
GDP in Nov from 4% of GDP in Oct. Going forward, we expect expenditure
growth to be range bound while revenues could improve due to seasonal
patterns. We estimate the fiscal deficit at 3.5% of GDP in F2019.
For important disclosures, refer to the Disclosure Section,
located at the end of this report.
1

F2019 Outlook - Growth Recovery on Track
4Q18 growth tracking modestly below our expectations: Recent high-frequency growth data have been mixed,
which means 4Q18 growth is tracking modestly slower at 7.2% vs. our earlier estimate of 7.4%. Notwithstanding
this slight moderation, we do expect growth to be supported in the near term by lower oil prices, election-related
spending and support to liquidity conditions at the margin. As such, we see downside risk of about 10-20bp to our
F2019 growth estimate of 7.6%, reflecting the weaker-than-expected growth in QE Sept. However, we believe that
the landscape for growth has improved with a pickup in capex and capacity utilization, which keeps us confident
that GDP growth should be around 7.6% in F2020.
Inflation outlook – likely to remain benign in the near term: Given the lower-than-expected recent inflation data
and benign trend in drivers of inflation (food and fuel prices), we expect inflation to average 3.9% in F2020.
Indeed, inflation will likely remain sub-3% in 1Q19 and rise above 4% in F2H20. However, we expect core inflation to
remain higher at 4.8% in F2020.
Monetary policy – expect an extended pause with a neutral stance: With inflation expected around the 4% mark
and key macro factors turning benign – i.e., trend in oil prices and lower pressure from strength in the US dollar,
we expect RBI to maintain status quo in rates with a neutral stance. Indeed, we expect the MPC to change stance
to neutral in the February policy review and maintain rates on hold through F2020.
What about a rate cut in the base case? In our view, the factors that should play in favour of a pause are: 1) core
inflation is still above headline, which can risk anchoring inflation expectations lower; 2) monetary transmission
will be difficult, as deposit growth has remained below credit growth, putting pressure on the credit deposit ratio.
With RBI’s flexible inflation targeting framework, its key policy aim would be to anchor inflation expectations
lower, and in this context we do not see room for RBI to take up preemptive monetary easing.
Risks tilted to the downside: In our view, the risks to the outlook are tilted to the downside and stem mainly from
external factors. The key swing factors to track from the external indicators will be strength of US dollar/rates,
potential spillovers in the global capital market environment and the extent of trade tensions affecting global
growth. From a domestic perspective, the key swing factors will be the outcome of general elections in 2019,
domestic credit conditions and the pace of capex.
2

Key Macro Indicators – What They Are Saying
Positive
Negative
1. Oil consumption growth improved in December 1. Both services and manufacturing PMI slowed in December
2. Headline CPI moderated to a 18 month low of 2.2%
2. IIP growth moderated significantly, partly on account of festival
related holidays
3. Trade deficit improved to a 10 month low of US$ 13.1 Bn 3. Commercial vehicle sales contracted by 7.8% in Dec-18
4. FX reserves improved at the margin
4. Two wheeler sales and passenger car sales declined in Dec-
18
3

Focus Charts
Key Charts for the Month
Exhibit 1: High Frequency Indicators Moderated in December
QE Sep Oct Nov Dec
Broad Market Corporate Revenue 14.8% - - -
Manufacturing PMI 52.1 53.1 54.0 53.2
Medium & Heavy Commercial Vehicle Sales 26.3% 17.8% -11.0% -20.7%
Credit Growth 12.8% 14.6% 15.1% 15.1%
IIP 5.2% 8.4% 0.5% -
Core Industries' Output 5.4% 4.7% 3.5% -
-----Cement Production 12.5% 18.5% 8.9% -
-----Steel Production 4.7% 2.6% 6.0% -
Exports 11.0% 17.9% 0.8% 0.4%
Non Oil Non Gold Imports 10.4% 11.1% -6.5% -2.2%
Two-Wheeler Sales 5.1% 17.2% 7.1% -2.2%
Passenger Vehicle Sales -3.6% 1.6% -3.4% -0.4%
Electricity/Power Demand 7.6% 7.1% 7.7% -
Oil Consumption 1.3% 4.2% -1.9% 3.2%
Source: CEIC, Haver, CMIE, Morgan Stanley Research
Exhibit 2: Credit Growth Remains Healthy
17.0
Flow of financial resources to commercial sector Bank Credit
15.0
13.0
11.0
9.0
7.0
5.0
Jun-17 Sep-17 Dec-17 Mar-18 Jun-18 Sep-18 Dec-18
Source: CEIC,RBI, Morgan Stanley Research. Note: Financial resources include non food bank credit, investment in CP, shares and bonds/debentures
Exhibit 3: Trade Deficit Narrowed to a 10-Month Low in December
-2%
-3%
-4%
-5%
-6%
-7%
-8%
Trade Balance % GDP
-9%
Monthly Annualized 3-Month Trailing Sum Annualized
-10%
Dec-14 Jun-15 Dec-15 Jun-16 Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
Source: CEIC, Morgan Stanley Research.
Exhibit 4: Headline CPI Moderates While Core Remains Higher in December
7%
6%
5%
4%
3%
Headline CPI
Core - Ex Food & Fuel
New CPI (combined) YoY%
5.7%
5.6%
2%
Core Core - Ex Food, Fuel, Petrol/Diesel
2.2%
& Housing
1%
Jun-15 Dec-15 Jun-16 Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
Source: CEIC, Morgan Stanley Research
4

Where Are We in the Growth Cycle?
Growth weakened more than expected in 3Q-18, though investment trend remained robust. With capacity utilisation picking up, we expect this momentum to sustain. Election related spending and liquidity easing will support growth. We
remain constructive on our 2019 growth estimate of 7.6%
Exhibit 5: Stylised Representation of Growth Recovery Cycle
Macro adjustment, weak trend in
domestic demand.
Domestic demand still weak.
External demand slows sharply.
Macro adjustment
complete. Growth improves
led by public capex and
FDI, weakness in external
demand intensifies.
Growth recovery broadens,
with pickup in consumption.
Exports back on recovery
track from Sep-16.
Currency Replacement
Program (CRP) in Nov-16
delayed the domestic
demand recovery.
CRP impact faded from
2Q17. Implementation of
GST impacted production in
late June / July but
economy has since
recovered in Aug / Sep.
Clear runway for growth
with consumption and
exports strengthening and
public capex and FDI
remaining supportive.
Growth momentum improved
with consumption, exports
picking up. Nascent signs of
revival in private capex
Growth momentum to sustain
with uptick in capex and
steady consumption spending
Public Capex
Private Capex
FDI
Consumption
Exports
Sharp decline in
global commodity
prices, EM shock
Currency
replacement
shock to
consumption
recovery
Source: Morgan Stanley Research
2016
2013 2014 2015 2017
2018
2019E
5

Snapshot: Key Growth Indicators
Exhibit 6: Key macro indicators (dark green colour denotes top 10 percentile growth; dark blue colour is bottom 10 percentile growth)
Source: CEIC, RBI, CMIE, PPAC, Morgan Stanley Research
6

I. Growth Indicators
Corporate Profitability Expected to Improve with Decline in Oil Prices
Exhibit 7: Nominal Corporate Revenue Growth (ex-Energy & Financials) – Broad Market*
Exhibit 8: Nominal Corporate Revenue Growth (BSE500, ex-Energy and Financials)*
16%
14%
12%
10%
Corpoarte Revenue (ex energy, fin) 14.8%
12%
10%
8%
Real BSE 500 Revenue Growth (ex energy, fin)
10.8%
8%
6%
6%
4%
2%
4%
2%
0%
Sep-15
Dec-15
Mar-16
Jun-16
Sep-16
Dec-16
Mar-17
Jun-17
Sep-17
Dec-17
Mar-18
Jun-18
Sep-18
0%
-2%
Sep-15
Dec-15
Mar-16
Jun-16
Sep-16
Dec-16
Mar-17
Jun-17
Sep-17
Dec-17
Mar-18
Jun-18
Sep-18
Exhibit 9: Nominal Corporate Revenue Growth (ex-Energy and Financials) – Broad Market* v/s Nominal
IP
Corporate Revenue Growth (Broad Market)
Nominal IP, 3MMA, (RS)
Exhibit 10: Real Corporate Revenue and Real Industry GVA Growth
18%
16%
Real Corporate Revenue (on WPI ex food) ex energy, fin
Real Industry GVA
26%
21%
16%
11%
6%
1%
Sep-11
Mar-12
Sep-12
Mar-13
Sep-13
Mar-14
Sep-14
Mar-15
Sep-15
Mar-16
Sep-16
Mar-17
Sep-17
Mar-18
Sep-18
23%
18%
13%
8%
3%
-2%
-7%
14%
12%
10%
8%
6%
4%
2%
0%
-2%
Sep-15
Dec-15
Mar-16
Jun-16
Sep-16
Dec-16
Mar-17
Jun-17
Sep-17
Dec-17
Mar-18
Jun-18
Sep-18
Source: Capitaline, CEIC, Morgan Stanley Research
* Corporate revenue growth is based on the performance of 2812 companies (for broad market), 399 companies (for BSE 500).
7

QE Dec-18 GDP Growth Tracking at 7.2% YoY
Exhibit 11: Trend in GDP and GVA Growth (YoY, %)
Exhibit 12: Contribution to GDP Growth
10%
Growth, YoY%
15%
Consumption GCF Net Exports Discrepancies GDP
9%
GDP
10%
8%
7%
7.1%
6.9%
5%
6%
0%
5%
4%
Sep-12
Mar-13
Sep-13
Mar-14
GVA
Sep-14
Mar-15
Sep-15
Mar-16
Sep-16
Mar-17
Sep-17
Mar-18
Sep-18
-5%
Sep-12
Mar-13
Sep-13
Mar-14
Sep-14
Mar-15
Sep-15
Mar-16
Sep-16
Mar-17
Sep-17
Mar-18
Sep-18
Exhibit 13: GVA by Industry, YoY (%)
Exhibit 14: Quarterly Nominal GDP, YoY(%)
11%
GVA By Industry (YoY% Growth)
17%
Quarterly Nominal GDP (YoY% Growth)
9%
15%
7%
5%
3%
12%
10%
12.0%
1%
-1%
-3%
Services
Industry
Agriculture and allied activities
7%
Sep-12
Sep-12
Mar-13
Sep-13
Mar-14
Sep-14
Mar-15
Sep-15
Mar-16
Sep-16
Mar-13
Mar-17
Sep-13
Sep-17
Mar-14
Mar-18
Sep-14
Sep-18
Mar-15
Sep-15
Mar-16
Sep-16
Mar-17
Sep-17
Mar-18
Sep-18
Source: CEIC, Morgan Stanley Research
8

IIP Growth Moderated Significantly Led by Festival Related Holidays
Exhibit 15: Industrial Production (IIP) Growth
Exhibit 16: Core Infrastructure Index
10%
YoY%
YoY%, 3MMA
YoY% Weight in IP Oct-17 Nov-17 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18
Infrastructure Index 40.27 5.0% 6.9% 4.0% 7.8% 7.3% 4.7% 4.3% 4.7% 3.5%
8%
6%
4%
2%
0%
Dip in Nov-18
reading due to
festive related
holidays
--Coal 4.16 3.9% 0.8% 12.0% 11.5% 9.7% 2.5% 6.5% 11.3% 3.7%
--Crude Oil 3.62 -0.4% 0.2% -2.9% -3.4% -5.4% -3.7% -4.2% -5.0% -3.5%
--Natural Gas 2.77 2.9% 2.4% -1.4% -2.7% -5.1% 1.0% -1.7% -1.0% 0.6%
--Refinery Products 11.29 7.5% 8.2% 4.9% 12.1% 12.3% 5.0% 2.5% 1.3% 2.3%
--Fertilizers 1.06 3.0% 0.3% 8.4% 0.9% 1.3% -5.2% 2.6% -11.6% -8.1%
--Steel 7.21 8.6% 14.5% -0.1% 4.2% 6.9% 4.0% 3.2% 2.6% 6.0%
--Cement 2.16 -1.3% 16.9% 13.0% 14.2% 11.1% 14.7% 11.8% 18.5% 8.9%
--Electricity 7.99 3.2% 3.9% 4.2% 8.5% 6.7% 7.6% 8.2% 10.8% 5.4%
Nov-14
Feb-15
May-15
Aug-15
Nov-15
Feb-16
May-16
Aug-16
Nov-16
Feb-17
May-17
Aug-17
Nov-17
Feb-18
May-18
Aug-18
Nov-18
Exhibit 17: Total Oil Consumption
Exhibit 18: Services and Manufacturing PMI
14%
11%
Total Petroleum Products Consumption
YoY% YoY% 3MMA
14%
11%
56
54
Services PMI
Manufacturing PMI
Expansion
8%
8%
52
5%
5%
2%
2%
-1%
-1%
-4%
-4%
-7%
-7%
Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
50
48
46
44
Dec-14
Jun-15
Dec-15
Jun-16
Contraction
Dec-16
Jun-17
Dec-17
Jun-18
Dec-18
Source: CEIC, Haver, PPAC, Morgan Stanley Research
9

Auto Sales Weakened Across Segments
Exhibit 19: Two-wheeler Sales
45%
Domestic Two Wheeler Sales
35%
YoY% YoY% 3MMA
25%
15%
5%
-5%
-15%
-25%
Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 20: Passenger Car Sales
40% Domestic Passenger Vehicle Sales
30%
YoY% YoY% 3MMA
20%
10%
0%
-10%
-20%
Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 21: Domestic Retail Sales Growth (Consumer Staples Companies’ Sales Growth)*
20%
15%
10%
5%
0%
Domestic FMCG Sales
Real Retail Sales (deflated by CPI)
The pickup in retail sales in Dec-17
was partly due to base effects.
Exhibit 22: Consumer Durables Production
18%
YoY%
13%
8%
3%
YoY%, 3MMA
-5%
-10%
Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Sep-16 Sep-17 Sep-18
-2%
-7%
Nov-14 May-15 Nov-15 May-16 Nov-16 May-17 Nov-17 May-18 Nov-18
Source: CEIC, Company Data, Morgan Stanley Research
* Underlying data from FY17 onward is not comparable to previous years due to change in accounting standards. However, YoY growth rates remain comparable, as reporting companies adjust for changes in the base years as well. From
Sep-17 quarter, YoY growth numbers would have been affected, as companies have switched to the GST regime.
10

Labour Market – Online Hiring Activity Improved in December
Exhibit 23: Naukri Job Index – Overall Employment Trend
Exhibit 24: Naukri Job Index – Employment by Sector
23%
18%
13%
8%
3%
-2%
Naukri Job Index
YoY% 3MMA
YoY%
Dec-17 Feb-18 Apr-18 Jun-18 Aug-18 Oct-18 Dec-18
Naukri Job Index YoY%
24%
Auto and Auto Ancillary
31%
18%
Construction and Engineering
-6%
31%
Banking and Financial Services
4%
6%
Insurance
27%
Capital Goods
-2%
45%
Dec-18
Oil and Gas
11%
4%
Overall
8%
Dec-17
3%
10%
BPO and ITeS
8%
IT- Software
14%
-11% 2%
Pharma & Biotech
1%
10%
Telecom
-25% 0% 25% 50%
Exhibit 25: EPFO – Addition to Payroll
Exhibit 26: Trend in Employment from PMI Surveys
19
17
15
13
11
9
7
5
3
1
New EPF Subscribers between Sep-17 and Oct-18 (in Mn)
18-25Y Total
Sep-17
Oct-17
Nov-17
Dec-17
Jan-18
Feb-18
Mar-18
Apr-18
May-18
Jun-18
Jul-18
Aug-18
Sep-18
Oct-18
54
53
52
51
50
49
48
Jun-16
PMI Manufacturing Employment
Expansion
Sep-16
Dec-16
Mar-17
Jun-17
Sep-17
PMI Services Employment
Contraction
Dec-17
Mar-18
Jun-18
Sep-18
Dec-18
Source: Naukri Infoedge, CMIE, Morgan Stanley Research
Note: For Naukri Job Index, total no. of new jobs posted in July 2008 was scaled to 1000. Index for subsequent months is relative to Jul-08.
11

Uptick in Capital Goods Imports; Healthy Trend in Cement Production
Exhibit 27: Trend in Capital Goods Imports
40%
30%
20%
10%
0%
-10%
-20%
Capital Good Imports
YoY% 3MMA
YoY%
-30%
Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 28: Steel Production and Demand
10%
9%
YoY%, 3MMA
Steel Demand Steel Production
8%
7%
6%
5%
4%
3%
2%
1%
0%
Sep-17 Dec-17 Mar-18 Jun-18 Sep-18 Dec-18
Exhibit 29: Trend in Cement Production
28%
24%
20%
16%
12%
8%
4%
0%
-4%
-8%
-12%
-16%
YoY%
YoY% 3MMA
Nov-15 May-16 Nov-16 May-17 Nov-17 May-18 Nov-18
28%
24%
20%
16%
12%
8%
4%
0%
-4%
-8%
-12%
-16%
Exhibit 30: Medium & Heavy and Light Commercial Vehicle Sales
90% MHCV, YoY, 3MMA, LS LCV, YoY, 3MMA, RS
41%
75%
60%
31%
45%
21%
30%
11%
15%
1%
0%
-15%
-9%
-30%
-19%
-45%
-29%
Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Source: CEIC, Morgan Stanley Research
12

Projects Under Implementation Improved; Private Projects Registered Positive Growth
Exhibit 31: Projects Under Implementation (Quarterly)*
Exhibit 32: New Investment Projects
20.0%
15.0%
Projects under implementation - YoY%
Public Private Total
30,000
25,000
Total Public Private
New Investment Projects, Rs bn (4Q trailing sum)
10.0%
5.0%
20,000
15,000
10,000
0.0%
5,000
-5.0%
-10.0%
Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
0
Dec-08 Dec-10 Dec-12 Dec-14 Dec-16 Dec-18
Exhibit 33: Engineering & Construction Companies' Order Flows#
80%
Order Inflows, Quarterly
Order Inflows, Trailing 4Q Sum, RS
60%
Order Book, Quarterly, RS
40%
20%
0%
-20%
-40%
-60%
Dec-15
Mar-16
Jun-16
Sep-16
Dec-16
Mar-17
Jun-17
Sep-17
Dec-17
Mar-18
Jun-18
Sep-18
40%
30%
20%
10%
0%
-10%
-20%
-30%
Exhibit 34: Capacity Utilisation vs. Investment
80
78
76
74
72
70
Mar-10
Dec-10
Sep-11
Jun-12
Mar-13
Dec-13
Capacity Utilization, 4Q Moving
average, (pushed forward by 3-
quarters), LS
GFCF (% of GDP), 4Q- Moving Sum
Sep-14
Jun-15
Mar-16
Dec-16
Sep-17
Jun-18
Mar-19
37
35
33
31
29
27
25
Source: CMIE, CEIC, Haver, Company Data, Morgan Stanley Industrials Team, Morgan Stanley Research
* Includes all government and private projects in various stages of implementation.
# Order book flows include data from Siemens, L&T (Domestic), ABB, Thermax, Nagarjuna Const, Hindustan Const and Simplex Infrastructures Ltd.
13

Capex – Slowdown in New Residential Launches and Sales
Exhibit 35: New Launches vs. New Sales (Pan-India Residential)
125%
105%
85%
65%
45%
25%
5%
-15%
-35%
-55%
2Q15
3Q15
New Launches (YoY)
New Sales (YoY)
4Q15
1Q16
2Q16
3Q16
4Q16
1Q17
2Q17
3Q17
4Q17
1Q18
2Q18
3Q18
4Q18
46.8%
9.2%
Exhibit 36: Absorption Rate (Pan-India Residential)
4,90,000
4,70,000
4,50,000
4,30,000
4,10,000
3,90,000
3,70,000
3,50,000
3,30,000
3,10,000
2,90,000
Active Vacancy / Unsold Inventory (Units), LHS
Absorption Rate - RHS
4Q12
1Q13
2Q13
3Q13
4Q13
1Q14
2Q14
3Q14
4Q14
1Q15
2Q15
3Q15
4Q15
1Q16
2Q16
3Q16
4Q16
1Q17
2Q17
3Q17
4Q17
1Q18
2Q18
3Q18
4Q18
15%
13%
11%
9%
7%
5%
Exhibit 37: New Sales Trend (Key Cities, Pan-India Residential)
Exhibit 38: All-India House Price Index*
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
No of units
Bangalore Mumbai Pune Greater
Mumbai
4Q17 1Q18 2Q18 3Q18 4Q18
Hyderabad Chennai Noida Kolkata Gurgaon
9%
7%
5%
3%
1%
Three-City Residential Property Price
Index (MS Property Team)*
YoY%
-2%
Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Source: Jones Lang La Salle – REIS India, RBI Morgan Stanley Research
* MS Property team index includes cities of Mumbai, Bangalore, NCR.
14

Services – Slowdown in Cargo Traffic Movement
Exhibit 39: Rail Freight
10%
8%
6%
4%
2%
0%
-2%
YoY%
YoY% 3MMA
10%
-2%
-4%
-4%
Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
8%
6%
4%
2%
0%
Exhibit 40: Seaport Cargo Traffic
YoY%
YoY% 3MMA
12%
12%
9%
9%
6%
6%
3%
3%
0%
Dec-14 Dec-15 Dec-16 Dec-17
0%
Dec-18
Exhibit 41: Air Cargo Handled
19%
14%
YoY%
YoY% 3MMA
19%
14%
Exhibit 42: Air Traffic – Hours Flown
35%
YoY%
30%
25%
YoY%, 3MMA
9%
4%
9%
4%
20%
15%
10%
-1%
Nov-14
May-15
Nov-15
May-16
Nov-16
May-17
Nov-17
May-18
Nov-18
-1%
5%
0%
Nov-14 Jul-15 Mar-16 Nov-16 Jul-17 Mar-18 Nov-18
Source: CEIC, Morgan Stanley Research
15

Services – Internet Users Rose in QE Sep
Exhibit 43: Air Passenger Traffic – Number of Passengers Flown
25%
25%
20%
20%
15%
15%
10%
10%
5%
YoY
YoY,3MMA
5%
0%
0%
-5%
Nov-13 Nov-14 Nov-15 Nov-16 Nov-17 Nov-18
Exhibit 44: Tourist Arrivals
22% YoY% YoY% 3MMA
22%
17%
17%
12%
12%
7%
7%
2%
2%
-3%
Nov-13 Nov-14 Nov-15 Nov-16 Nov-17
-3%
Nov-18
Exhibit 45: Mobile Subscriber Base Growth
Exhibit 46: Internet Subscriber Base Growth
1100
1000
900
800
700
600
500
Cellular Subsriber Base, Mn, LS
Cellular Subscriber Base Growth, YoY%, RS
25%
20%
15%
10%
5%
550
500
450
400
350
300
250
In MN, LS
Total Internet Users
YoY%, RS
33%
28%
23%
18%
13%
400
0%
Nov-16 May-17 Nov-17 May-18 Nov-18
200
Sep-14
Dec-14
Mar-15
Jun-15
Sep-15
Dec-15
Mar-16
Jun-16
Sep-16
Dec-16
Mar-17
Jun-17
Sep-17
Dec-17
Mar-18
Jun-18
Sep-18
8%
Source: CEIC, TRAI, Morgan Stanley Research
16

Government Finances – Fiscal Deficit Narrowed in Nov-18
Exhibit 47: Central Government Fiscal Policy – Key Indicators
Exhibit 48: Trend in Expenditure and Receipts
76%
66%
56%
46%
65.5% 64.6% 63.8% 65.1% 66.7% 66.1%
48.4% 47.6%
Apr-Nov Revenue Receipts (as % of annual receipts)
April-Nov Expenditure (as % of annual expenditure)
52.4%
57.6%
53.4%
49.3%
36%
26%
16%
6%
F2014 F2015 F2016 F2017 F2018 F2019 BE
Exhibit 49: Government Finances – Summary
YoY%
Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 FY19BE FY18
Total Receipts 95.6 14.0 22.5 -25.0 6.7 2.3 -15.8 -10.9 12.0 7.6
Revenue Receipts 101.4 16.4 21.5 -25.9 8.4 6.5 -8.0 7.1 14.6 4.3
--Net Tax Revenue 149.8 0.5 22.9 -31.2 -11.0 7.3 -14.2 7.3 16.6 12.8
--Gross Tax Revenue 58.7 7.8 14.1 -14.5 -1.9 8.6 -4.5 10.3 16.7 11.9
--Direct 5.9 -45.8 22.1 8.0 88.7 18.0 12.5 17.8 14.4 18.6
--Indirect 124.5 26.6 5.9 -28.0 -23.2 -7.7 -15.1 6.8 19.2 5.6
--Non Tax 8.9 231.6 -1.0 12.1 52.8 -8.2 31.1 5.8 3.9 -29.9
Capital Receipts -45.2 -82.5 38.8 4.7 -57.5 -76.4 -87.4 -69.5 39.1 76.8
Total Expenditure -7.7 15.1 22.4 15.5 27.5 17.4 6.2 -15.9 9.6 10.1
--Revenue Expenditure -17.2 20.4 20.2 20.5 25.7 25.3 8.5 -13.7 13.0 11.5
--Interest Payments -6.1 3.1 2.3 -19.6 16.9 10.7 31.0 7.6 3.1 8.3
--Capital Expenditure 62.8 -28.3 46.9 -9.1 43.8 -17.2 -11.8 -32.8 1.0 -9.2
Total expd ex subsidy ex interest 4.7 23.5 23.8 5.0 26.2 29.0 -16.2 13.9 11.7 11.6
Revenue Deficit -40.5 21.7 17.7 129.2 263.1 263.1 -52.7 -52.7 0.6 43.8
Fiscal Deficit -26.1 15.4 22.3 76.0 153.3 153.3 -113.2 -113.2 -2.8 10.9
Exhibit 50: Total Expenditure – Revenue vs. Capital (YoY %)
Central Government Expenditure YoY%
Total
Revenue Capital
Monthly 12M Trailing 12M Trailing 12M Trailing
Oct-17 16.5 10.2 6.1 39.8
Nov-17 37.1 12.0 8.0 40.4
Dec-17 20.3 13.2 9.3 40.7
Jan-18 -4.7 11.4 7.0 41.8
Feb-18 17.6 11.7 6.3 49.2
Mar-18 -35.3 8.5 11.5 -9.2
Apr-18 -7.7 3.4 4.9 -5.5
May-18 15.1 1.0 3.0 -11.2
Jun-18 22.4 4.1 6.3 -8.8
Jul-18 15.5 4.6 7.3 -10.9
Aug-18 27.5 6.6 8.9 -7.2
Sep-18 17.4 9.6 12.4 -7.2
Oct-18 6.2 9.0 13.4 -15.3
Nov-18 -15.9 5.1 9.3 -18.4
Source: CEIC, Morgan Stanley Research Note: Data for central government accounts
17

II. External Indicators
Broad Based Moderation in Exports Growth
Exhibit 51: Export Growth
Exhibit 52: Trend in Exports Growth in INR Terms
40%
30%
20%
10%
0%
-10%
-20%
Exports
YoY%
Non Oil Exports (RS)
80%
60%
40%
20%
0%
-20%
40%
30%
20%
10%
0%
-10%
-20%
Exports growth in INR
terms
YoY%
YoY, 3MMA
-30%
-40%
Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Jun-14
Dec-14
Jun-15
Dec-15
Jun-16
Dec-16
Jun-17
Dec-17
Jun-18
Dec-18
Exhibit 53: Seasonally Adjusted Export Trend
110
105
100
95
90
Exports Seasonally Adjusted, 3MMA, Index
Oct-14=100
Exhibit 54: India’s Share in Global Goods Exports
2.1% India Exports as % of World Exports
1.9%
1.7%
Monthly 6M trailing
1.5%
1.3%
1.1%
85
0.9%
80
Mar-15
Aug-15
Jan-16
Jun-16
Nov-16
Apr-17
Sep-17
Feb-18
Jul-18
Dec-18
0.7%
0.5%
Sep-00 Sep-03 Sep-06 Sep-09 Sep-12 Sep-15 Sep-18
Source: CEIC, Haver, Morgan Stanley Research
18

Oil Exports Slowed; Non Oil Exports Contracted
Exhibit 55: Exports by Segment
Exports - by product
Dec's % Share in
Total
Nov- 18,
YoY%
Dec-18,
YoY%
Engineering Goods 25.6% -16.4% -3.1%
Gems & Jewellery 9.3% -16.9% -19.2%
Petroleum Products 15.1% 42.7% 13.2%
Organic & Inorganic Chemicals 7.2% 12.3% 5.5%
Drugs & Pharmaceuticals 5.9% 3.2% -0.7%
Ready-made Garments of All Textiles 4.9% 9.0% 2.8%
Cotton Yarn/Fabrics/made-ups, Handloom Products 3.2% -5.3% -5.5%
Marine Products 2.2% -15.1% -7.4%
Plastic & Linoleum 2.7% 28.6% 20.2%
Rice 2.3% -23.1% 1.3%
Others 21.5% 11.9% 9.8%
Total 100.0% 0.8% 0.4%
Exhibit 56: Exports by Segment – YoY % 3MMA
Engg Goods
Oil
Gems & Jewellery
Textiles / Garments
70%
Chemicals
Commodity ex oil
55%
3MMA, YoY
40%
25%
10%
-5%
-20%
Dec-16 Mar-17 Jun-17 Sep-17 Dec-17 Mar-18 Jun-18 Sep-18 Dec-18
Exhibit 57: Exports by Destination (Share, Apr- Nov F2019)
Exhibit 58: Exports by Destination (Nov-18)*
150 India Exports Index, SA, May 2012=100, 3MMA
140
EU US UAE AXJ
130
120
110
100
90
80
70 % of Exports (2018)
60
EU: 18% US: 16% UAE:8% AXJ: 37%
Nov-15 May-16 Nov-16 May-17 Nov-17 May-18 Nov-18
Source: CEIC, Ministry of Commerce, Morgan Stanley Research. *Country share as per March-18
19

Services Trade Balance Remained Steady in Nov-18
Exhibit 59: Net Services Exports
75%
Net Services Exports
Exhibit 60: Services Trade Balance (% of GDP)
4.5%
55%
YoY
YoY, 3MMA
4.0%
35%
3.5%
15%
3.0%
-5%
-25%
Nov-12
May-13
Nov-13
May-14
Nov-14
May-15
Nov-15
May-16
Nov-16
May-17
Nov-17
May-18
Nov-18
2.5%
2.0%
Nov-13
Service balance, monthly annualised (% GDP)
Services balance, 3M trailing sum, annualised (% GDP)
May-14
Nov-14
May-15
Nov-15
May-16
Nov-16
May-17
Nov-17
May-18
Nov-18
Exhibit 61: Net Software Services Exports
25%
20%
15%
10%
5%
0%
YoY%
Exhibit 62: Net Services Exports by Segment
YoY%
Share in
Sep-17 Dec-17 Mar-18 Jun-18 Sep-18
Total
(Sep-18)
--Services 12.8% 16.5% 8.8% 2.1% 10.2% 100.0%
--- Travel 61.6% 14.5% -2.7% -61.1% -24.9% 6.0%
--- Transportation -92.9% -105.9% -147.5% -0.2% -1523.5% -2.2%
--- Miscellaneous 13.7% 21.2% 17.0% 8.4% 16.2% 95.5%
-----Software Services 1.8% 1.1% 5.8% 5.5% 7.3% 95.2%
-----Business Services 297.2% -96.0% -521.1% 113.6% 40.6% -1.4%
-----Financial Services 395.9% 42.7% -221.5% -932.3% -171.1% 0.9%
-----Communication Services -6.9% -46.4% -27.1% -6.7% 2.2% 1.6%
---Others 64.9% -25.6% 0.9% 54.4% -74.9% 0.6%
-5%
Sep-10 Sep-12 Sep-14 Sep-16 Sep-18
Source: Haver, CEIC,, RBI, Morgan Stanley Research
20

Imports Growth Declined by 2.4% in December
Exhibit 63: Imports, Non-oil Imports (YoY%)
Imports Non Oil Imports Non oil non gold
35%
YoY% 3MMA
35%
20%
20%
5%
5%
-10%
-10%
-25%
Dec-15 Jun-16 Dec-16 Jun-17 Dec-17 Jun-18
-25%
Dec-18
Exhibit 64: Oil and Gold Imports (YoY%)
85%
75%
Gross Oil , LS
Gold & Silver, RS
200%
65%
YoY% 3MMA
150%
55%
45%
100%
35%
50%
25%
0%
15%
5%
-50%
-5%
-100%
Dec-16 Mar-17 Jun-17 Sep-17 Dec-17 Mar-18 Jun-18 Sep-18 Dec-18
Exhibit 65: Oil, Gold and Non-oil Non-gold Imports (Monthly percentage of GDP Annualised)
% of GDP, Annualised
15%
13%
12%
10%
9%
7%
6%
4%
Non oil non gold & silver, LS
3%
Gross Oil , LS
1%
Gold & Silver, RS
0%
Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
3%
2%
1%
Exhibit 66: Seasonally Adjusted Imports (in Dollars, Indexed)
160
140
120
100
80
Seasonally Adjusted Indexed Oct 2014=100
Imports
60
Non Commodity Non Oil Non Gold
60
Commodity Imports (Inc. Oil and Gold)
40
40
Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
160
140
120
100
80
Source: CEIC, Morgan Stanley Research
21

Gold and Silver Imports Contracted Substantially
Exhibit 67: Imports by Segment
Imports - by product
Dec's % Share in
Total
Nov- 18,
YoY%
Dec-18,
YoY%
Petroleum, Crude & products 26.0% 41.3% 3.2%
Electronic goods 10.4% 0.3% -9.1%
Gold 6.3% -15.6% -24.3%
Machinery, electrical & non-electrical 7.5% 7.7% 8.4%
Pearls, precious & Semi-precious stones 6.2% -46.2% -28.1%
Coal, Coke & Briquettes, etc. 5.5% 12.5% 11.4%
Organic & Inorganic Chemicals 4.4% 10.8% 2.7%
Transport equipment 4.6% -21.8% -14.7%
Artificial resins, plastic materials, etc. 2.9% 11.1% 5.4%
Iron & Steel 3.5% 17.6% 15.6%
Others 22.7% -8.0% 5.0%
Total 100.0% 4.3% -2.4%
Exhibit 68: Imports by Segment – YoY% 3MMA
55%
Total
Electronics -RS 3MMA, YoY
80%
45%
Machinery
60%
Coal, Coke
Pearls, precious & Semi-precious stones(RS) 40%
35%
20%
25%
0%
15%
-20%
5%
-40%
Dec-17 Feb-18 Apr-18 Jun-18 Aug-18 Oct-18 Dec-18
Exhibit 69: Imports by Destination (Share, Apr-Nov F2019)
Exhibit 70: Imports by Destination (Nov18)
India Imports Index, SA May 2012=100, 3MMA
165
145
125
EU China USA UAE + S. Arabia AXJ
% of Imports (F2018 )
UAE+Saudi Arabia: 9.5%
EU: 10.3% China 16.5%
105
85
65
45
Nov-13 Nov-14 Nov-15 Nov-16 Nov-17 Nov-18
Source: CEIC, Ministry of Commerce, Morgan Stanley Research
22

Goods Trade Deficit Moderated to a 10-Month Low
Exhibit 71: Trade Balance (% of GDP)
-2%
-3%
-4%
-5%
-6%
-7%
Trade Deficit % of GDP
-8%
Monthly, annualized
-9%
3-month trailing sum, annualized
-10%
Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 72: Gross Gold Imports (% of GDP)
Gross Gold Imports As % of GDP
4%
6M trailing
12M trailing
3%
2%
1%
Dec-06 Dec-08 Dec-10 Dec-12 Dec-14 Dec-16 Dec-18
Exhibit 73: Trade Balance, 12M Trailing (% of GDP)
1%
12M Trailing, % of GDP
-1%
-3%
-5%
1%
-1%
-3%
-5%
Exhibit 74: Current Account Deficit (% of GDP)
8% Current Account Balance Quarterly Annualized, % of GDP
6%
Overall Current Account
CAD ex oil (% GDP)
4%
4Q Trailing Sum
2%
0%
-7%
-7%
Trade Deficit
-9%
Trade deficit ex net gold -9%
-11%
Trade deficit ex net gold net oil
-11%
Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
-2%
-4%
4Q Trailing Sum
-6%
-8%
Sep-04 Sep-06 Sep-08 Sep-10 Sep-12 Sep-14 Sep-16 Sep-18
Source: RBI, CEIC, Morgan Stanley Research
23

Net Oil Imports Softened
Exhibit 75: Trend in Commodity Trade Balance
Exhibit 76: Commodity Trade Deficit (% of GDP)
-1%
3M trailing sum as % of GDP
-4%
-4.5%
-4.8%
-7%
-7.1%
12M trailing sum as % of GDP
-10%
Dec-08 Dec-10 Dec-12 Dec-14 Dec-16 Dec-18
0%
-1%
-2%
-3%
-4%
-5%
-6%
-7%
-8%
-2.2%
F2004
F2005
Commodity Trade
Balance % of GDP
F2006
F2007
F2008
-6.9%
F2009
F2010
-6.5%
F2011
F2012
F2013
F2014
F2015
F2016
F2017
-3.5%
F2018
Exhibit 77: Trend in Net Oil Imports
6.0%
5.5%
5.0%
4.5%
4.0%
3.5%
3.0%
2.5%
2.0%
Dec-10
Net Oil Imports (12M Trailing Sum, %
of GDP)
Jun-11
Dec-11
Jun-12
Dec-12
Jun-13
Dec-13
Jun-14
Dec-14
Jun-15
Dec-15
Jun-16
Dec-16
Jun-17
Dec-17
Jun-18
Dec-18
Exhibit 78: Sensitivity of Macro Variables to Higher Commodity Prices**
*total subsidy (which can be shared between government and oil companies).
Source: CEIC, Morgan Stanley Research.
**MS Oil and Gas Research Team, RBI, Morgan Stanley Research Estimates
24

Capital Flows – FDI flows Slowed Down; Early Signs of FII Outflows
Exhibit 79: FII Flows – Equity and Debt (US$ bn)
Exhibit 80: Monthly ECB / FCCB^ Flows (US$ bn)
9
Debt, LS Equity, LS Total (12M trailing sum), RS
40
6
Monthly, LS
12M Trailing Sum, RS
35
7
30
5
3
20
1
10
-1
0
-3
-5
-10
-7
-20
Jan-17 May-17 Sep-17 Jan-18 May-18 Sep-18 Jan-19
5
4
3
2
1
0
Nov-13
May-14
Nov-14
May-15
Nov-15
May-16
Nov-16
May-17
Nov-17
May-18
Nov-18
30
25
20
15
10
Exhibit 81: Monthly Gross FDI Inflows (US$ bn)
Exhibit 82: NRI Deposit Flows (US$ bn)
80
70
60
50
40
Gross FDI Inflows
12M trailing sum (US$ bn), LS
12M trailing sum % of GDP, RS
FDI flows as % of GDP (12M trailing
sum) at 2.3%
3.2%
2.8%
2.4%
2.0%
1.6%
3
2
1
34
24
14
30
1.2%
20
0.8%
10
0.4%
0
0.0%
Nov-09 Nov-10 Nov-11 Nov-12 Nov-13 Nov-14 Nov-15 Nov-16 Nov-17 Nov-18
0
4
Non Resident Ordinary Rupee Accounts
-1 Non Resident External Rupee Accounts
-6
Foreign Currency Non Resident Accounts
-2 Total 12M trailing sum, RS
-16
Nov-14 May-15 Nov-15 May-16 Nov-16 May-17 Nov-17 May-18 Nov-18
Source: RBI, CEIC, Bloomberg, Morgan Stanley Research
^ ECB = External Commercial Borrowing, FCCB = Foreign Currency Convertible Bond
25

External Balance Sheet – External Debt Remains Steady
Exhibit 83: FX Reserves (US$bn)*
470
445
420
395
370
345
320
295
270
US$ bn
245
Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
445
426
FX Reserves
397
395
FX Reserves, Adjusted
for Fwd
Exhibit 84: Months of Import Cover
16
15
Import cover using total FX Reserves
14
13
12
11
10
9
8
9.3 x
7
6
Dec-06 Dec-08 Dec-10 Dec-12 Dec-14 Dec-16 Dec-18
Exhibit 85: External Debt
Sep-17 Dec-17 Mar-18 Jun-18 Sep-18
Total external debt US $ bn 495 513 530 514 510
Total external debt % of GDP 20.4 20.1 20.5 20.4 20.8
Short-term debt by original maturity US $ bn 93 98 102 99 104
Short-term (inc. residual maturity) US $ bn 207 218 222 221 223
FX Reserves US$ bn 400 409 424 406 401
Total external debt
% of FX
124 125 125 127 127
Imports cover (FX reserves/Avg
monthly imports)
Reserves
# of
months
11.1 10.9 10.9 10.2 9.6
Exhibit 86: Net International Investment Position (% of GDP)
-15%
Net IIP % of GDP
-16%
-17%
-18%
-19%
Sep-12 Sep-13 Sep-14 Sep-15 Sep-16 Sep-17 Sep-18
Source: RBI, CEIC, Haver, Morgan Stanley Research. *- FX Reserves data is till 11th Jan 2019
26

Exchange Rate – Less Volatility in US$/INR
Exhibit 87: US$/INR and EUR/INR
75
US$/INR, LS EUR/INR, RS
95
70
85
65
60
75
55
65
50
45
Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18
55
Jan-19
Exhibit 88: AXJ FX Performance (vs. US$)
15%
10%
5%
0%
-5%
-10%
13.2%
-4.4%
% change
2017 2018 YTD + shows appreciation
- shows depreciation
10.1% 10.5%
9.2%
8.2%
6.5%
6.7%
1.8%
-2.8%
2.7%
0.8%
Korea Taiwan India Singapore Thailand Malaysia China
-5.6%
Exhibit 89: Trend in Real Effective Exchange Rate (REER)*
124
RBI REER Trade Weighted 36 Currencies
120
116
Mean + SD
112 Mean
108
104
Mean -SD
100
96
Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
Exhibit 90: RBI Real Effective Exchange Rate* (REER – CPI adjusted, 36-country) vs Commodity Trade
Balance
124
120
116
112
108
104
100
RBI REER Trade Weighted 36 Currencies, LS
Commodity Trade Balance, 12M trailing (% GDP),
RS
-2.5%
-3.5%
-4.5%
-5.5%
-6.5%
96
-7.5%
Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
Source: Bloomberg, RBI, CEIC, Morgan Stanley Research. Note: Jan-19 data for REER is MS Estimate.
27

Exchange Rate – Continued Intervention in Currency Market by the RBI
Exhibit 91: FX Reserves Accretion* (3M trailing, US$ bn)
30
20
10
US$ 23.4 bn
Exhibit 92: FX Reserves (12M change, US$ bn)
20
15 FX Reserves (12M Change, US$ bn)
10
5
0
0
-5
-10
-10
-20
-15
-20
-67.2
-30
Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
China
India
Indonesia
Hong Kong
Philippines
Malaysia
Thailand
Singapore
Taiwan
Korea
Exhibit 93: RBI FX Intervention (Spot, US$ bn)
Exhibit 94: Outstanding RBI FX Intervention (Forwards, US$ bn)
9
7
RBI Fx intervention - Spot (US$ bn)
Negative shows - RBI sold dollars
5
3
1
-1
-3
-0.6
-5
-7
-9
-7.2
Nov-16 May-17 Nov-17 May-18 Nov-18
40
35
30
25
20
15
10
5
0
RBI Fx intervention Outstanding Net Forwards (US$
bn)
Negative shows - RBI
sold dollars
-5
-1.9
Nov-16 Mar-17 Jul-17 Nov-17 Mar-18 Jul-18 Nov-18
Source: Bloomberg, RBI, CEIC, Morgan Stanley Research . *FX Reserves data is till 11th Jan 2019.
28

III. Inflation Indicators
Headline CPI Moderated; Core Remained Elevated
Exhibit 95: CPI New Index (2012 = 100, YoY %)
9%
7%
5%
3%
1%
Headline CPI
Core - Ex Food & Fuel
New CPI (combined) YoY%
5.7%
2.2%
-1%
Core Core - Ex Food, Fuel,
Petrol/Diesel & Housing
Food CPI
-2.5%
-3%
Jun-15 Dec-15 Jun-16 Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
5.6%
Exhibit 96: CPI Index – Detail by Segment (YoY %)
Headline
Food
Non Food
Non Fuel
Food &
Beverages
Pan,Tobacco Clothing &
& Intoxicants Footwear
Housing Fuel & Light Misc
Weights 100.0 39.1 44.9 45.9 2.4 6.5 10.1 6.8 28.3
Nov-17 4.9% 4.4% 4.9% 4.4% 7.9% 5.0% 7.4% 8.2% 3.7%
Dec-17 5.2% 5.0% 5.1% 4.9% 7.8% 4.9% 8.2% 7.9% 3.8%
Jan-18 5.1% 4.7% 5.1% 4.6% 7.6% 4.9% 8.3% 7.7% 3.8%
Feb-18 4.4% 3.3% 5.2% 3.5% 7.3% 4.9% 8.3% 6.9% 3.8%
Mar-18 4.3% 2.8% 5.4% 3.1% 7.7% 4.9% 8.3% 5.7% 4.2%
Apr-18 4.6% 2.8% 5.9% 3.0% 7.9% 5.1% 8.5% 5.2% 5.0%
May-18 4.9% 3.1% 6.2% 3.3% 8.0% 5.5% 8.4% 5.8% 5.4%
Jun-18 4.9% 2.9% 6.4% 3.1% 8.1% 5.6% 8.4% 7.2% 5.7%
Jul-18 4.2% 1.3% 6.3% 1.7% 6.3% 5.3% 8.3% 8.0% 5.8%
Aug-18 3.7% 0.3% 5.9% 0.8% 5.4% 4.9% 7.6% 8.6% 5.6%
Sep-18 3.7% 0.5% 5.8% 1.0% 5.6% 4.6% 7.1% 8.6% 5.6%
Oct-18 3.4% -0.9% 6.2% -0.1% 6.1% 3.6% 6.6% 8.5% 6.7%
Nov-18 2.3% -2.6% 5.7% -1.7% 6.1% 3.5% 6.0% 7.2% 6.2%
Dec-18 2.2% -2.5% 5.7% -1.5% 5.8% 3.5% 5.3% 4.5% 6.5%
Exhibit 97: Contribution to Food Inflation (% point contribution): By Component
Exhibit 98: CPI Inflation Outlook
7%
5%
Cereals Meat and Fish Egg Milk
Oils and Fats Fruits Vegetables Pulses
Sugar Spices Food CPI
7%
6%
MSe
3%
5%
1%
4%
-1%
3%
Headline
-3%
-5%
% pt contribution
Feb-18 Apr-18 Jun-18 Aug-18 Oct-18 Dec-18
2%
Core- non food non fuel
Core-core, non food non fuel,
non housing
1%
Mar-15 Sep-15 Mar-16 Sep-16 Mar-17 Sep-17 Mar-18 Sep-18 Mar-19 Sep-19 Mar-20 Sep-20 Mar-21
Source: CEIC, Morgan Stanley Research Estimates
29

WPI Inflation Moderated Led by Lower Food and Fuel Prices
Exhibit 99: Headline WPI
AXJ ex India PPI WPI WPI - Non food manufactured products
6%
India WPI Base Year: 2012
6%
4.2%
YoY%
3.8%
3%
3%
2.6%
-1%
-4%
-7%
Dec-13
Jun-14
Dec-14
Jun-15
Dec-15
Jun-16
Dec-16
Jun-17
Dec-17
Jun-18
Dec-18
-1%
-4%
-7%
Exhibit 100: Non-Food, Non-Global Commodity WPI
10%
8%
6%
4%
2%
Inflation Base Year: 2012
2.3%
-1%
YoY% 3MMA
-3%
Non Food YoY%
-5%
Non Food Non Global Commodity
-7%
YoY%
YoY% 3MMA
-9%
Dec-14 Jun-15 Dec-15 Jun-16 Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
5.2%
Exhibit 101: Seasonally Adjusted Sequential Momentum
14%
9%
WPI, SAAR, 3MMA
4%
1.0%
-1%
7.8%
-6%
-11%
Non food WPI, SAAR, 3MMA
-16%
Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 102: WPI Index – Detail by Segment (YoY%)
Overall
Food
Global
Commodities (ex
Mineral Oil)
Fuel
Non Food
Non Global
Commodity
Non Food
Inflation
Weights 100 25 26 13 35 75
Nov-17 4.0% 4.2% 5.9% 8.4% 1.6% 4.0%
Dec-17 3.6% 2.8% 5.7% 8.0% 1.6% 3.9%
Jan-18 3.0% 1.7% 6.3% 4.7% 1.5% 3.6%
Feb-18 2.7% 0.5% 7.5% 4.6% 1.1% 3.7%
Mar-18 2.7% 0.4% 7.4% 4.7% 1.1% 3.7%
Apr-18 3.6% 1.0% 8.0% 8.0% 1.5% 4.7%
May-18 4.8% 1.5% 10.0% 12.7% 1.7% 6.2%
Jun-18 5.7% 1.9% 11.3% 16.5% 1.9% 7.3%
Jul-18 5.3% -0.4% 11.5% 18.1% 2.5% 7.8%
Aug-18 4.6% -1.6% 11.0% 17.7% 2.3% 7.4%
Sep-18 5.2% 0.5% 11.0% 17.3% 2.0% 7.3%
Oct-18 5.5% -0.2% 11.8% 18.7% 2.4% 8.0%
Nov-18 4.6% -1.5% 10.2% 16.3% 2.7% 7.3%
Dec-18 3.8% 0.4% 8.2% 8.4% 2.3% 5.2%
Source: CEIC, Morgan Stanley Research
30

Food Inflation – Sequential Pick Up in High Frequency Food Prices Though Trend Remains Muted
Exhibit 103: High-frequency Retail Food Prices (MoM%)
Retail Prices (MoM) Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Dec-18 Jan-19
Cereals 0.0% 0.8% 0.2% 0.1% 0.9% 0.6% 0.5% 0.0%
Pulses -0.8% 0.7% 0.4% -0.3% -0.3% 1.2% 1.3% 0.5%
Milk 1.0% 0.3% -0.2% -0.5% 0.4% -0.9% 0.8% 0.0%
Oils and Fats -0.1% 0.6% -0.2% 0.1% 0.3% 0.2% 0.1% -0.2%
Onion Potato Tomato 29.4% 7.1% 0.1% -6.3% 0.3% 1.0% -10.4% -3.8%
Sugar 3.7% 1.1% 0.2% -0.7% 0.2% -0.4% -0.8% -0.1%
Condiments and Spices 0.0% 0.5% 0.5% -0.7% -0.2% 0.5% 0.3% 1.2%
Exhibit 104: High-frequency Retail Food Prices v/s Food CPI (YoY%)
12%
10%
8%
6%
4%
2%
0%
-2%
-4%
-6%
YoY%
High Frequency Retail Prices- YoY
CPI - Food
Retail Food prices aggregated using
CPI weights (approx 32% wt), to
proxy the CPI-Food component
-8%
Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19
Exhibit 105: High-frequency Retail Food Prices (MoM%)
Exhibit 106: High-frequency Retail Food Price Index
110
105
100
2016
2017
2018
2019
5Yr Avg
High Frequency Food price Index
95
90
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Source: CEIC, Dept. of Consumer Affairs, Morgan Stanley Research
31

Both Retail and International Fuel Prices Moderated
Exhibit 107: RBI Survey of Inflation Expectations
16
14
12
10
8
6
3 Month Ahead
One Year Ahead
RBI - Household Inflation
Expectation Survey
4
Nov-08 Nov-10 Nov-12 Nov-14 Nov-16 Nov-18
Exhibit 108: Commodity Prices (INR Terms, Index Jan 2010=100)
210
Jan-10 = 100 (in INR Terms)
190
170
150
130
110
90
CRB Food Index
CRB Commodity Index
70
Brent Crude
50
Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
Exhibit 109: Brent: Indian Basket (INR/bbl), YoY%
Exhibit 110: Four City Average of Retail Oil Prices
85%
65%
45%
25%
5%
-15%
-35%
India Crude Oil Basket (INR/bbl) YoY%
90
85
80
75
70
65
60
55
50
45
40
Retail fuel prices (Rs/lt)
Petrol Diesel
-55%
Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19
Jan-14
Jul-14
Jan-15
Jul-15
Jan-16
Jul-16
Jan-17
Jul-17
Jan-18
Jul-18
Jan-19
Source: RBI, Bloomberg, Haver, Morgan Stanley Research
32

Wages – Rural Wage Growth Remains Benign
Exhibit 111: Rural Wage Growth
23%
21%
19%
17%
15%
13%
11%
9%
7%
5%
Rural Wage
Rural Farm Wage
YoY% 3MMA
3%
Oct-08 Oct-10 Oct-12 Oct-14 Oct-16 Oct-18
Exhibit 112: Rural Wages Sequential Momentum
2015 2016
2.0%
2017 5Y Avg
1.5%
2018 Rural Wage, MoM
1.0%
0.5%
0.0%
-0.5%
-1.0%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Exhibit 113: Proxy for Trend In Urban Income (YoY%)
Exhibit 114: Proxy for Trend in Urban Income
50%
40%
4Q trailing average
BSE 500 Employee Cost Growth
12%
11%
Employee Cost (as % of net sales)
30%
20%
10%
9%
8%
10%
7%
4Q trailing average
0%
6%
Sep-06
Jun-07
Mar-08
Dec-08
Sep-09
Jun-10
Mar-11
Dec-11
Sep-12
Jun-13
Mar-14
Dec-14
Sep-15
Jun-16
Mar-17
Dec-17
Sep-18
Sep-06
Jun-07
Mar-08
Dec-08
Sep-09
Jun-10
Mar-11
Dec-11
Sep-12
Jun-13
Mar-14
Dec-14
Sep-15
Jun-16
Mar-17
Dec-17
Sep-18
Source: RBI, Labour Bureau, Capitaline, Morgan Stanley Research
Note: The Labour Bureau released a new wage series starting from Nov 2013. We have used the MoM change from the new series from Jan-14 onwards. For Nov and Dec 2013, we used the 5Y avg MoM change from the old series.
33

IV. Monetary Indicators
M3 Growth Remains Steady
Exhibit 115: Reserve Money – Contribution to Growth
Exhibit 116: Currency in circulation (% of GDP)**
60%
40%
Net RBI Credit to Govt
Govt's Currency Liabilities
M0 YoY%
Net RBI Credit to Comm Sector
Net FX Accretion*
13%
12%
11%
10%
Currency in circulation % of GDP
12.1%
11.1%
20%
9%
0%
-20%
8%
7%
6%
6.3%
-40%
Dec-16 Jun-17 Dec-17 Jun-18 Dec-18
Jan-10
Oct-10
Jul-11
Apr-12
Jan-13
Oct-13
Jul-14
Apr-15
Jan-16
Oct-16
Jul-17
Apr-18
Jan-19
Exhibit 117: Money Multiplier
9.0
8.5
2 month moving avg
8.0
7.5
7.0
6.5
6.0
5.5
5.0
4.5
Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 118: Trends in Component of Money Supply
60%
YoY, % M3 M1 Reserve Money
45%
30%
15%
0%
-15%
-30%
Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Source: RBI, Bloomberg, CEIC, Morgan Stanley Research. *Net FX accretion is net foreign assets less net non-monetary liabilities. ** Jan-19 data as of 11th Jan 2019
34

Deposit Growth Improved; Credit Growth Moderated at the Margin
Exhibit 119: Credit Growth vs. Deposit Growth*
24%
Credit Deposit
21%
YoY%
18%
15%
14.5%
12%
9%
9.9%
6%
3%
Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
Exhibit 120: Credit Growth – Nominal vs. Real*
18%
13%
8%
3%
YoY%
Nominal Credit Growth
Real Credit Growth (on WPI 2012)
Real Credit Growth (on CPI)
-3%
Nov-14 Nov-15 Nov-16 Nov-17 Nov-18
18%
13%
8%
3%
-3%
Exhibit 121: Credit Growth by Segment
27
22
Agriculture & Allied Activities
Industry ex Infra
Services Non food credit growth by
Infrastructure sector (YoY%,3MMA)
26.5
Exhibit 122: Trend in Flow of Financial Resources to Commercial Sector from Banking Sector*
17.0
Flow of financial resources from SCBs,YoY(%)
15.0
17
16.4
12
7.2
7
7.2
2
1.4
-4
-9
Nov-13 Nov-14 Nov-15 Nov-16 Nov-17 Nov-18
13.0
11.0
9.0
7.0
5.0
Jun-17 Sep-17 Dec-17 Mar-18 Jun-18 Sep-18 Dec-18
Source: RBI, CEIC, CMIE, Morgan Stanley Research
Note: Using CPI industrial workers until 2012, CPI ((combined) from Jan-12 onwards. *:Financial resources include non food bank credit, investment in CP, shares and bonds/debentures. *Jan-19 data as of 4th Jan 2019
35

Moderation in Commercial Paper Issuance in December
Exhibit 123: NBFCs Share in Total System Credit
Exhibit 124: Trend in Bank Credit to NBFCs
20%
18%
16%
14%
NBFCs
HFCs
65%
55%
45%
Bank Credit to NBFCs
YoY(%)
YoY(%), 3MMA
12%
10%
8%
6%
35%
25%
15%
4%
2%
0%
F2011 F2012 F2013 F2014 F2015 F2016 F2017 F2018
5%
-5%
Nov-12
May-13
Nov-13
May-14
Nov-14
May-15
Nov-15
May-16
Nov-16
May-17
Nov-17
May-18
Nov-18
Exhibit 125: Spread between AAA 1Y and BBB 1Y Corporate Bond
Exhibit 126: Weekly Issuance of Commercial Paper
3.7
3.5
3.3
Spread of 1Y BBB corporate bonds over
1Y AAA corporate bonds
1800
1600
1400
1200
CP Amount Issued (in INR, Bn)
3.1
1000
800
2.9
2.7
Jan-18
Feb-18
Mar-18
Apr-18
May-18
Jun-18
Jul-18
Aug-18
Sep-18
Oct-18
Nov-18
Dec-18
Jan-19
600
400
200
0
30-Jan-18
28-Feb-18
31-Mar-18
30-Apr-18
31-May-18
30-Jun-18
31-Jul-18
31-Aug-18
30-Sep-18
31-Oct-18
30-Nov-18
31-Dec-18
Source: RBI, Bloomberg, MS India Financial Team, Morgan Stanley Research
36

Deposit Growth Improved in Both Real and Nominal Terms
Exhibit 127: Deposit Growth – Nominal vs. Real
Exhibit 128: Demand and Time Deposits – Contributions to Deposit Growth
18%
13%
YoY%
Nominal Deposit Growth
Real Deposit Growth (on WPI 2012)
Real Deposit Growth (on CPI)
18%
13%
16%
12%
%pt contribution
Demand Deposit
Time Deposit
16%
12%
8%
8%
8%
8%
3%
3%
4%
4%
-3%
-3%
Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19
0%
0%
Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
Exhibit 129: Credit-Deposit Ratio vs. Investment-Deposit Ratio
Exhibit 130: Credit-Deposit Ratio – Scenario Analysis
Credit Deposit Ratio,LS Investment Deposit Ratio, RS
80%
35%
78%
34%
33%
76%
32%
74%
31%
30%
72%
29%
70%
28%
27%
68%
26%
Dec-14 Dec-15 Dec-16 Dec-17 Dec-18
81%
79%
77%
75%
73%
71%
69%
67%
Dec-13
Scenario 1: Credit growth at 10.5% Deposit growth at 7.5%
Scenario 2: Credit growth at 13.5% Deposit growth at 7.7%
Scenario 3: Credit growth at 12.5% Deposit growth at 8.1%
Current credit growth at 14.5%
Deposit growth at 9.9%
Jun-14
Dec-14
Jun-15
Dec-15
Jun-16
Dec-16
Jun-17
Dec-17
Jun-18
MS Scenarios
Dec-18
Jun-19
Source: RBI, CEIC, Morgan Stanley Research estimates
Note: Using CPI industrial workers until 2012, CPI (urban) from Jan-12 onwards.
37

Interbank Liquidity Improving at the Margin
Exhibit 131: Daily Interbank Liquidity Balance
100
80
Interbank Liquidity (US$ bn)
60
40
20
0
-20
-40
-60
May-12
Sep-12
Jan-13
May-13
Sep-13
Jan-14
May-14
Sep-14
Jan-15
May-15
Sep-15
Jan-16
May-16
Sep-16
Jan-17
May-17
Sep-17
Jan-18
May-18
Sep-18
Jan-19
Exhibit 132: Government Surplus Cash Balances Reckoned for Auction (Rs bn)
1800
1600
1400
1200
1000
800
600
400
200
Government of India Surplus Cash Balance Reckoned for
Auction (INR Bn)
0
Jan-18 Mar-18 May-18 Jul-18 Sep-18 Nov-18 Jan-19
Exhibit 133: Open Market (OMOs) and Secondary Market Operations (RBI Purchases of G-secs)
580
480
380
280
180
80
-20
-120
-220
Apr-16
RBI Conducted 9 OMO sales b/w
Jun-17 and Nov-17
Jul-16
Oct-16
Jan-17
Apr-17
Jul-17
Oct-17
RBI announced OMO purchases of
INR 500 Bn for Jan-19; OMO
purchases to continue untill Mar-19
Jan-18
Apr-18
Jul-18
Oct-18
Jan-19
Exhibit 134: Interbank Rate vs. Policy Rate Band
9%
9%
Reverse Repo Rate Repo Rate
Interbank Rate
MSF
8%
8%
7%
7%
6%
6%
5%
Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19
Source: RBI, Bloomberg, Morgan Stanley Research.
Note: Liquidity balance is reverse repo less repo amount outstanding.
38

Rates – G-Sec Yields Eased a Tad
Exhibit 135: 91-day T-bill vs. 10Y G-sec Yield (%)
8.5
8.0
7.5
7.0
6.5
6.0
10Y G-sec Yield
91D T-Bill Yield
5.5
Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19
Exhibit 136: Corporate Bond Yield Spreads
A
BBB
10Y Corporate bond yield spreads over 10Y government
AA
AAA
bond
4.2%
3.7%
3.2%
2.7%
2.2%
1.7%
1.2%
0.7%
0.2%
Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
Exhibit 137: 3M Commercial Paper (CP) vs. 3M Certificate of Deposit (CD)* Rate
9.6
3M CD Rate
9.6
9.1
3M CP Rate
9.1
8.6
8.6
8.1
8.1
7.6
7.6
7.1
7.1
6.6
6.6
6.1
6.1
5.6
5.6
Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19
Exhibit 138: Trend in Deposit and Lending Rates
10.5
10.0
9.5
9.0
8.5
8.0
7.5
7.0
6.5
SBI Base Rate
SBI Deposit Rate (1Y)
SBI 1Y MCLR
6.0
Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
Source: RBI, Bloomberg, SBI Corporate Website, Morgan Stanley Research
* Commercial paper is used as a substitute for a bank loan and is a short-term money market instrument which matures within a period of 270 days; a certificate of deposit is a document issued by the bank to an investor who chooses to
deposit funds in the bank for a specific amount of time.
Note: We have taken the peak rate around 1Y deposit rates from SBI (6.95% for 456 days to less than two years).
39

Real Rates Remained Steady
Exhibit 139: Real 10Y G-sec Yield
Exhibit 140: Real 91-Day T-bill Yield
Exhibit 141: Real 3M CP Rate
Exhibit 142: Real 3M CD Rate
Source: Bloomberg, CEIC, Morgan Stanley Research
40

Real Policy Rate – Remains Positive
Exhibit 143: Real Policy Rate (adj. for WPI)
14%
14%
12%
Real Policy Rate (on New-WPI) 12%
10%
10%
8%
8%
6%
6%
4%
4%
2%
2%
0%
Jan-14 Jan-15 Jan-16 Jan-17 Jan-18
0%
Jan-19
Exhibit 144: Real Policy Rate (adj. for CPI)
6%
4%
2%
0%
-2%
-4%
-6%
-8%
-10%
-12%
6%
4%
2%
0%
-2%
-4%
-6%
Real Policy Rates (on New CPI)
-8%
-10%
-12%
Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
Exhibit 145: Real Deposit Rate (SBI 1Y, adj. for WPI)
13%
Real 1Y Deposit Rate (on New WPI)
11%
9%
7%
5%
3%
1%
Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19
Exhibit 146: Real Deposit Rate (SBI 1Y, adj. for CPI)
6%
4%
2%
0%
-2%
-4%
-6%
-8%
Avg. real deposit
rate during 2003-07
was at 1.3%, while avg.
real deposit growth rate
was at 12.9%
Real 1Y Deposit Rate (on CPI IW)
Real 1Y Deposit Rate (on CPI)
-10%
Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
Source: RBI, SBI Corprate Website, CEIC, Morgan Stanley Research
Note: Policy rate used is repo rate except for July-13 to Dec-13, when the marginal standing facility (MSF) rate was used.
41

Real Rate Differentials – Sufficient Buffer with US Rates
Exhibit 147: Real 3M Rate (adj. for CPI)
6.0
India US US (on core CPI)
6.0
4.0
4.0
2.0
2.0
0.0
0.0
-2.0
-2.0
-4.0
Real 3M Tbill Rates (3MMA)
-4.0
-6.0
-6.0
Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
Exhibit 148: Real 10Y Rate (adj. for CPI)
5.5
4.0
India
US (on core CPI)
2.5
1.0
-0.5
-2.0
-3.5
Real 10Y Rates (3MMA)
-5.0
Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
Exhibit 149: Real 3M Rate Spread (adj. for CPI)
7.0
5.0
3.0
1.0
-1.0
-3.0
Spread of India Real 3M Tbill Rates over US
Spread of India Real 3M Tbill
Rates over US (based on US core
CPI, India headline CPI, 3MMA)
-5.0
-5.0
Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
7.0
5.0
3.0
1.0
-1.0
-3.0
Exhibit 150: Real 10Y Rate Spread (adj. for CPI)
5.0
3.0
1.0
-1.0
-3.0
Spread of India Real 10Y
rates over US (based on
US core CPI, India
headline CPI, 3MMA
Spread of India Real 10Y rates over US (based
on US, India headline CPI, 3MMA)
-5.0
-5.0
Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 Jan-19
5.0
3.0
1.0
-1.0
-3.0
Source: Bloomberg, CEIC, Morgan Stanley Research
42

Asset Quality – Banking System's Impaired Loan Ratio Remained Broadly Stable in QE-Sep
Exhibit 151: Banking System – Impaired Loan Ratio
12%
Impaired Loans Ratio^
11.5 12.0
11.1
9.9
GNPLs Restructured Loans
11.3
10%
9.2
7.6
8%
6.9
6.0
6%
5.1
3.4
4%
2%
0%
F2008 F2009 F2010 F2011 F2012 F2013 F2014 F2015 F2016 F2017 F2018 1HF19
Exhibit 152: Banking System – Sector Impaired Loan Ratio
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Minning
(% of advances of their
resoective sector)
Food Processing
Textiles
Paper
Chemicals
Plastic, Rubber
Cement
Mar-16 Mar-17 Mar-18 Sep-18
Basic Metal
Engineering
Vehicles
Gems & jewellery
Construction
Infrastructure
Exhibit 153: State-owned Banks – Impaired Loan Ratio
Exhibit 154: Ratio of Rating Upgrades to Downgrades (Crisil)
4.0%
3.0%
Gross Slippages, % of Trailing 12M Gross Loans
2.1x
1.8x
Credit Ratio (Upgrades to downgrades)
1.68x
1.88x
1.67x 1.68x
2.0%
1.0%
1.5x
1.2x
0.9x
0.6x
0.91x
0.62x
0.79x
1.29x
1.20x 1.22x
0.0%
F3Q16
F4Q16
F1Q17
F2Q17
F3Q17
F4Q17
F1Q18
F2Q18
F3Q18
F4Q18
F1Q19
F2Q19
0.3x
0.0x
FY12 FY13 FY14 FY15 FY16 1HFY17 FY17 1HFY18 FY18 1HFY19
Source: Crisil Research, Company Data, Morgan Stanley India Banks Research Team, Morgan Stanley Research. For more details on sector wise impaired loan ratio, please refer to RBI's Financial Stability Report.
^ For all banks as per RBI.
43

Tracking Digital Transactions
Exhibit 155: Digital Retail Transactions (as % of GDP)
Exhibit 156: Cards PoS/Cash Withdrawals
12%
10%
8%
Digital Retail Transactions (as % of GDP)
70%
60%
50%
Cards: POS Transactions/ ATM Withdrawls
Volumes Values
6%
4%
2%
0%
40%
30%
20%
F2004
F2005
F2006
F2007
F2008
F2009
F2010
F2011
F2012
F2013
F2014
F2015
F2016
F2017
F2018
F1Q19
F2Q19
10%
0%
F2012 F2013 F2014 F2015 F2016 F2017 F2018 F1Q19 F2Q19
Exhibit 157: Adhaar Enrollments and Saturation Level
Exhibit 158: Trend in Direct Benefit Transfers
100%
95%
90%
85%
80%
75%
70%
Nov-16
Jan-17
Adhaar assigned
Aadhaar Saturation (%), LS
Mar-17
May-17
Jul-17
Sep-17
Nov-17
Jan-18
Mar-18
May-18
Jul-18
Sep-18
Nov-18
Jan-19
1400
1200
1000
800
600
400
200
0
(in INR, Bn)
1800
1600
1400
1200
1000
800
600
400
200
0
Cash
In Kind
Cash Schemes (RS)
In Kind Schemes (RS)
2013-14 2014-15 2015-16 2016-17 2017-18 2018-19
(FYTD)
400
350
300
250
200
150
100
50
0
(Number of Schemes)
Source: UIDAI, DBT, RBI, Morgan Stanley Research
Note: Digital Retail Transactions include Credit+Debit Cards, Immediate Payment Service (IMPS), Mobile Wallet (MWallet), and Other Prepaid Payment Instrument (PPI) Channels.
44

V. Public Finance Indicators
Deficit – Fiscal Deficit Narrowed in November, Remained Above Target
Exhibit 159: Fiscal Deficit (12M Trailing Sum Percentage of GDP)
6.5%
6.0%
Fiscal Deficit (12M Trailing, as % of GDP)
5.5%
5.0%
4.5%
4.0%
3.5%
3.8%
3.0%
Nov-12 Nov-14 Nov-16 Nov-18
Exhibit 160: Revenue Deficit (12M Trailing Sum Percentage of GDP)
5.0%
Revenue Deficit (12M Trailing, as % of GDP)
4.5%
4.0%
3.5%
3.0%
2.5%
2.8%
2.0%
1.5%
Nov-12 Nov-14 Nov-16 Nov-18
Exhibit 161: Expenditure and Revenue Growth (12M Trailing, YoY%)
Total Expenditure
Total Receipts
25%
12M trailing sum, YoY%
20%
15%
10%
5%
0%
Nov-12 Nov-13 Nov-14 Nov-15 Nov-16 Nov-17 Nov-18
Exhibit 162: Expenditure and Revenue Growth (12M Trailing Sum Percentage of GDP)
16%
15%
Total Expenditure Total Receipts
12M trailing sum, % of GDP
14%
13%
12%
11%
10%
9%
8%
Nov-10 Nov-12 Nov-14 Nov-16 Nov-18
Source: CGA, CEIC, Morgan Stanley Research
Note: CGA is recording finances in the central government accounts as per the usual practice of cash accrual basis. Hence, there is a gap in figures being reported under CGA and CBEC. .
45

Expenditure Growth Contracted Led by High Base of Comparison
Exhibit 163: Overall Expenditure (YoY%)
58%
48%
38%
28%
18%
8%
-2%
-12%
Total Expenditure
Revenue Expenditure
Capital Expenditure
12M trailing sum, YoY%
-22%
Nov-10 Nov-12 Nov-14 Nov-16 Nov-18
Exhibit 164: Overall Expenditure (% of GDP, Annualized)
16%
15%
14%
13%
12%
11%
Total Expenditure
Capital Expenditure - RS
Revenue Expenditure
12M trailing sum, % of GDP
annualised
2.4%
2.2%
2.0%
1.8%
1.6%
1.4%
10%
1.2%
Nov-10 Nov-12 Nov-14 Nov-16 Nov-18
Exhibit 165: Expenditure Breakdown (YoY%)
YoY%
Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18
Apr-Nov
2018
Apr-Nov
2017
Total Expenditure 22.4% 15.5% 27.5% 17.4% 6.2% -15.9% 9.1% 14.9%
Ministry of Defence -4.5% 5.1% 23.2% 41.7% 7.1% 2.3% 8.4% 25.8%
Department of Fertilizers 100.5% 135.8% 132.7% 38.5% 177.7% -42.4% 9.3% -14.3%
Department of Food & Public Dist. 64.6% 50.4% 38.4% -50.1% 28904.7% -7.2% 5.3% 9.9%
Interest Payments 10.7% 31.0% 7.6% 23.7% 14.1% 8.2% 12.4% 16.2%
Ministry of Petroleum & Natural Gas 19.7% 10486.7% 144.1% -92.6% 1038.4% -59.9% -4.7% 51.1%
Ministry of Rural Development 13.5% -19.7% 46.1% -21.2% 79.0% -15.0% 8.9% 13.6%
Transfers to States & UT Govts 7.9% 2.5% 4.7% -23.0% -41.4% -42.7% -10.7% 294.9%
Revenue Expenditure 20.2% 20.5% 25.7% 25.3% 8.5% 25.3% 9.8% 13.1%
Capital Expenditure 46.9% -9.1% 43.8% -17.2% -11.8% -17.2% 4.0% 29.3%
Total Expenditure ex subsidy ex interest 23.8% 5.0% 26.2% 29.0% -16.2% 29.0% 9.0% 16.5%
Exhibit 166: Expenditure Breakdown (% of GDP, Annualized)
Expenditure Breakdown (% of GDP, Annualized)
Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Apr-Nov Apr-Nov
2018 2017
Total Expenditure 15.8% 17.5% 16.3% 12.5% 12.3% 15.7% 10.2% 10.3% 13.3% 13.6%
Ministry of Defence 3.5% 6.4% 8.4% 10.6% 13.0% 15.5% 17.7% 19.8% 2.5% 2.5%
Department of Fertilizers 0.5% 0.7% 1.2% 1.5% 2.1% 2.5% 3.4% 3.6% 0.4% 0.5%
Department of Food & Public Dist. 3.4% 5.2% 6.2% 7.5% 8.3% 8.7% 9.2% 9.6% 1.2% 1.3%
Interest Payments 1.1% 5.2% 10.1% 12.4% 14.9% 17.2% 19.5% 23.0% 2.9% 2.9%
Ministry of Petroleum & Natural Gas 0.2% 0.5% 1.0% 1.0% 1.5% 1.5% 1.8% 1.8% 0.2% 0.3%
Ministry of Rural Development 1.5% 2.5% 3.1% 3.8% 4.3% 4.9% 5.1% 5.6% 0.7% 0.7%
Transfers to States & UT Govts 0.6% 1.0% 2.1% 2.8% 3.4% 3.7% 4.1% 4.5% 0.6% 0.7%
Revenue Expenditure 12.5% 16.3% 14.7% 10.8% 10.9% 13.7% 9.2% 9.4% 11.7% 11.9%
Capital Expenditure 3.3% 1.2% 1.6% 1.7% 1.4% 2.0% 1.0% 0.9% 1.6% 1.7%
Tota Expenditure ex subsidy ex interest 10.6% 11.1% 9.3% 8.3% 7.7% 12.4% 5.9% 5.9% 8.6% 8.8%
Source: CGA, CEIC, Morgan Stanley Research
Note: Data for central government accounts.
46

Revenue Receipts Picked Up; Non Debt Capital Receipts Declined
Exhibit 167: Total Receipts (YoY%)
Total Receipts (YoY %)
Monthly 3M Trailing 12M Trailing
Apr-18 95.6% 8.1% 9.1%
May-18 14.0% 4.0% 9.2%
Jun-18 22.5% 33.3% 10.6%
Jul-18 -25.0% 4.1% 7.8%
Aug-18 6.7% 3.6% 9.0%
Sep-18 2.3% -2.3% 6.5%
Oct-18 -15.8% -1.1% 7.4%
Nov-18 -10.9% -5.5% 6.9%
Exhibit 168: Total Receipts (% of GDP, Annualized)
Total Receipts (% of GDP)
Monthly 3M Trailing 12M Trailing
Apr-18 5.1% 10.8% 9.4%
May-18 3.9% 9.2% 9.3%
Jun-18 10.5% 6.4% 9.4%
Jul-18 4.9% 6.4% 9.1%
Aug-18 8.8% 8.0% 9.1%
Sep-18 15.5% 9.7% 9.0%
Oct-18 6.6% 10.2% 8.8%
Nov-18 5.9% 9.2% 8.7%
Exhibit 169: Receipts Breakdown (YoY%)
Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 FY19BE FY18
Total Receipts 95.6% 14.0% 22.5% -25.0% 6.7% 2.3% -15.8% -10.9% 12.0% 7.6%
Revenue Receipts 101.4% 16.4% 21.5% -25.9% 8.4% 6.5% -8.0% 7.1% 14.6% 4.3%
--Net Tax Revenue 149.8% 0.5% 22.9% -31.2% -11.0% 7.3% -14.2% 7.3% 16.6% 12.8%
--Gross Tax Revenue 58.7% 7.8% 14.1% -14.5% -1.9% 8.6% -4.5% 10.3% 16.7% 11.9%
--Direct 5.9% -45.8% 22.1% 8.0% 88.7% 18.0% 12.5% 17.8% 14.4% 18.6%
--Indirect 124.5% 26.6% 5.9% -28.0% -23.2% -7.7% -15.1% 6.8% 19.2% 5.6%
--Non Tax 8.9% 231.6% -1.0% 12.1% 52.8% -8.2% 31.1% 5.8% 3.9% -29.9%
Capital Receipts -45.2% -82.5% 38.8% 4.7% -57.5% -76.4% -87.4% -69.5% 39.1% 76.8%
Exhibit 170: Receipts Breakdown (% of GDP Annualized)
Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 FY19BE FY18
Total Receipts 5.1% 3.9% 10.5% 4.9% 8.8% 15.5% 6.6% 5.9% 9.8% 9.2%
Revenue Receipts 5.0% 3.9% 9.8% 4.7% 8.8% 15.3% 6.5% 5.4% 9.2% 8.6%
--Net Tax Revenue 4.1% 3.1% 9.4% 3.8% 5.0% 14.6% 5.2% 4.7% 7.9% 7.4%
--Gross Tax Revenue 8.0% 7.1% 12.6% 7.6% 8.7% 18.3% 8.9% 8.3% 12.1% 11.4%
--Direct 3.0% 0.9% 6.8% 3.6% 3.2% 12.6% 4.0% 2.8% 6.1% 5.8%
--Indirect 5.1% 6.1% 5.8% 4.0% 5.5% 5.7% 4.9% 5.5% 6.0% 4.9%
--Non Tax 0.9% 0.8% 0.5% 0.9% 3.8% 0.7% 1.3% 0.7% 1.3% 1.1%
Capital Receipts 0.1% 0.0% 0.7% 0.2% 0.1% 0.2% 0.1% 0.5% 0.6% 0.7%
Source: CGA, CEIC, Morgan Stanley Research Note: Data for central government accounts.
47

Tracking GST Collections
Exhibit 171: GST-related Recent Announcements
Date
Jan-19
Dec-18
Jul-18
May-18
Mar-18
Jan-18
Dec-17
Nov-17
Oct-17
Key Changes Announced
1) Approval was given to Kerela to implement disaster cess of upto 1% for two years.
2) Two Limits for GST registration and payment for goods suppliers were decided, i.e. INR 4 Mn and INR 2 Mn. States can decide which limit they want to implement.
1) Rationalisation of GST rates in 28% rate slab
2) Six Items were moved from 28% slab to lower slabs, including flight tickets to pligrmages, cinema tickets
1) Rationalisation of GST rates on a wide range of goods and services.
2) Taxpayers with turnover upto Rs 5 Crore are required to file quaterly returns, though GST payments continues to be monthly
3) Reverse charge mechanism deferred for an year
1) Simpler monthly filling of returns
2) GSTN to become a government entity
1) Inter state e-way bill to be rolled out from 1st April while intra state by 15th April. Pan India implementation is expected by 1st June.
2) Export promotion schemes are extended to 30th Sept 2018 from 31st March earlier
1) GST council revised GST rates on 29 goods and 53 services. This included cuts in the rates on 20-litre packaged drinking water, biodiesel, diamonds and precious stones,
sugar candies, tailoring services, amusement parks and low-cost housing construction services.
1) GST council decided to roll out e-way bill on trial basis by 16th Jan 2018
2) A nationwide e-way bill system for inter-state movement of goods on a compulsory basis will be notified from February 1, 2018
1) GST Council slashed tax rates on 178 items from 28% to 18%, leaving only about 50 items in highest tax slab
2) FMCG, restaurants are the main item groups where GST rates have been cut
3) Only demerit and sin goods to be taxed at 28%
1) Group of Ministers reported on proposed changes to composition scheme and GST changes for restaurants. These proposals will be taken up by the GST council in its next
meeting on Nov 9-10.
2) Hike the composition scheme threshold from Rs10 million to Rs15 million
3) Reduce composition rates to flat 1% for manufacturers and restaurants from 2% and 5% previously
4) Recommended that all GST payers be allowed to file quarterly returns, even for those paying taxes monthly
5) Reduce late filing fees to Rs50 / day from Rs200 / day.
Exhibit 172: GST Collections
CGST (Rs.
Bn)
IGST
(Rs. Bn)
SGST
(Rs. Bn)
Cess (Rs.
Bn)
Total (Rs,
Bn)
Returns
Filed (mn)
Apr-18 186.5 257.04 505.5 85.5 1034.6 6.0
May-18 158.7 491.2 216.9 73.4 940.2 6.2
Jun-18 159.7 495.0 220.2 81.2 956.1 6.5
Jul-18 158.8 499.5 222.9 83.6 964.8 6.6
Aug-18 153.0 498.8 211.5 76.3 939.6 6.7
Sep-18 153.2 500.7 210.6 79.9 944.4 6.7
Oct-18 164.6 534.2 228.3 80.0 1007.1 6.7
Nov-18 168.1 497.3 230.7 80.3 976.4 7.0
Dec-18 164.4 479.4 224.6 78.9 947.3 7.2
Exhibit 173: Tax Rates for Goods and Services under GST Rate Structure*
Tax Rate
0%
5%
12%
18%
Goods
Milk, eggs, fresh fish, newspapers,
handloom, salt
Spices, tea, coffee, frozen vegetables, coal,
rusk, medicines
Tooth powder, cellphones, namkeen,
packaged dry fruits, butter
Copper bars, rods and wires, steel products,
mineral water (exc 20lts), pastries & cakes,
infant use preparations, plastic products,
deodorants, shaving creams,washing
machine
28% Pan masala, automobiles, motorcycle,
Key Items
Healthcare, education
Services
Transport services including air travel in economy
class, leasing of aircrafts, restaurants including those
in hotel premises with room tariff upto INR 7500
Air transport in other than economy class, non a.c.
hotels, works contracts
Telecom services, renting of accommodation with per
day rental between INR 2500-7500, restaurants in
hotel premises which has room tariff above INR 7500,
supply of food/ drinks in outdoor catering, services
by way of admission to entertainment events such as
sporting events like Indian Premier League, cinema,
water parks, gambling
Accommodation in 5-star hotel where per day room
rent is above INR7500
Source: Central Board of Excise and Customs (CBEC), PIB, Morgan Stanley Research
48

Oil & Subsidy – Oil Subsidy Bill May Remain Range Bound As Global Oil Prices Normalise
Exhibit 174: Subsidy Burden to Stay Stable in F2019E
Exhibit 175: Brent (INR/bbl) vs. Oil Import Burden
2.6%
2.4%
2.2%
2.0%
1.8%
1.6%
1.4%
1.2%
1.0%
% of GDP
F2007
F2008
F2009
F2010
F2011
F2012
2.5%
F2013
F2014
F2015
F2016
Total Subsidy
1.6%
F2017
F2018RE
F2019BE
7000
6000
5000
4000
3000
2000
Dec-14
Jun-15
Brent (INR/bbl), LS
Net oil imports, 3M trailing annualised % of GDP, RS
Net oil imports, 12M trailing % of GDP, RS
Dec-15
Jun-16
Dec-16
Jun-17
Dec-17
Jun-18
Dec-18
7.0%
6.0%
5.0%
4.0%
3.0%
2.0%
1.0%
0.0%
Exhibit 176: Oil Subsidies and Oil Excise Revenue to Be Largely Steady*
2.0%
1.6%
As a % of GDP
1.8%
Oil subsidies Oil excise revenues
1.4%
1.5%
Exhibit 177: Cumulative Saving from Oil Gains Begins To Decline in F2018 as Incremental Gains
Diminish
2.0%
Rise in oil excise revenues since peak
Savings in oil subsidies since peak
Saving from lower oil
prices
began to decline in F2018
1.2%
0.8%
1.0%
0.7% 0.8%
0.7%
0.8%
0.5%
1.5%
1.0%
As a % of GDP
0.7%
1.0%
0.8%
0.4%
0.2% 0.2% 0.2%
0.0%
F2013 F2014 F2015 F2016 F2017 F2018
Source: Bloomberg, PPAC, CEIC, Morgan Stanley Research
0.5%
0.0%
0.1%
0.2% 0.5%
0.0%
0.7% 0.8% 0.7%
-0.5%
Source: PPAC, Morgan Stanley Research
F2014 F2015 F2016 F2017 F2018
Source: Bloomberg, PPAC, CEIC, Morgan Stanley Research (E) estimates
*F2018 Oil excise revenues are provisional
49

States' Fiscal Deficit Budgeted at 2.6% in F2019; Farm Loan Waiver in Focus
Exhibit 178: States' Overall Fiscal Deficit as Percentage of GDP*
5.0%
4.5%
4.0%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
States' Fiscal Deficit
F1995
F1996
F1997
F1998
F1999
F2000
F2001
F2002
F2003
F2004
F2005
F2006
F2007
F2008
F2009
F2010
F2011
F2012
F2013
F2014
F2015
F2016
F2017
F2018RE
F2019 BE
Exhibit 179: Overall Expenditure Breakdown for States
(INR, Bn)
F2014 F2015 F2016 F2017 F2018 (RE) F2019 (BE)
Revenue Expenditure 16372.9 18382.7 20868.9 25188 27837.8
Capital Expenditure 3015.5 4236 5100.5 5097.1 5754.4
% of GDP
F2015 F2016 F2017 F2018 (RE) F2019 (BE)
Revenue Expenditure 13.1% 13.4% 13.7% 15.0% 14.9%
Capital Expenditure 2.4% 3.1% 3.3% 3.0% 3.1%
YoY, %
F2015 F2016 F2017 F2018 (RE) F2019 (BE)
Revenue Expenditure 18.7% 12.3% 13.5% 20.7% 10.5%
Capital Expenditure 23.3% 40.5% 20.4% -0.1% 12.9%
Exhibit 180: Trend in State Fiscal Deficit
F2018 (RE) F2019 (BE)
F2018 (RE) F2019 (BE)
Himachal Pradesh 5.4 5.2 Tripura 7.7 2.9
Goa 4.6 4.8 Haryana 2.8 2.9
J&K 3.9 4.5 Karnataka 2.8 2.9
Punjab 4.5 3.9 Chhattisgarh 3 2.8
Telangana 3.2 3.5 Tamil Nadu 2.8 2.8
Odisha 3.5 3.4 Uttarakhand 2.6 2.8
Meghalaya 3.8 3.4 Andhra Pradesh 3.4 2.6
Madhya Pradesh 3.4 3.3 Jharkhand 2.5 2.5
Kerala 3.4 3.2 Manipur 3.5 2.4
Nagaland 6.6 3.2 Bihar 7.2 2
Assam 12.7 3.0 Arunachal Pradesh 2.8 2.0
Rajasthan 3.5 3.0 Maharashtra 1.8 1.8
Sikkim 3.5 3.0 West Bengal 2.4 1.7
Uttar Pradesh 3.1 3.0 Gujarat 1.7 1.7
Mizoram 3.2 1.0
Exhibit 181: State Wise Farm Loan Waiver Scheme*
Assam (0.2)
Farm Loan Waiver (in INR, bn)
Tamil Nadu (0.4)
Chhattisgarh (2.1)
Punjab (2.1)
Rajasthan (2.1)
Maharashtra (1.4)
Karnataka (2.6)
U.P. (2.6)
M.P. (5.4)
0 100 200 300 400
Source: RBI, Media Articles, Morgan Stanley Research. Note: (-)ive numbers in fiscal deficit tables indicate surplus. *Figures in () indicates farm loan waiver amount as % of GSDP, for states for which F2018 GSDP data was not available, we
have assumed constant growth in F2018 vs F2017.
50

Central Government Deficit – We estimate F2019 Fiscal Deficit at 3.5%
Exhibit 182: Tracking F2019 Accounts
INR bn
YoY%
F2019 F2019
F2019 F2019
F2018RE F2019 BE Apr-Nov (Dec-Mar) F2018 RE F2019BE Apr-Nov (Dec-Mar)
I. Revenue Receipts 15054 17257 8703 8554 9.5% 14.6% 8.1% 22.1%
(a) Tax Revenue (net to Centre) 12695 14806 7317 7490 15.3% 16.6% 4.6% 31.4%
-- Gross tax revenue 19461 22712 11647 11066 13.4% 16.7% 7.1% 28.8%
Indirect Taxes + Other Tax 9411 11212 6230 4982 8.6% 19.3% 0.1% 56.3%
-- Customs 1352 1125 1111 242 8.7% -8.2% -76.8%
-- Excise 2770 2596 2175 595 6.5% 14.2% -68.9%
-- GST 4446 7439 3819 3620 - 67.3% 50.0% 90.5%
Direct taxes 10050 11500 5417 6083 18.3% 14.4% 16.5% 12.7%
-- Corporation tax 5637 6210 2913 3297 16.3% 10.2% 16.6% 5.0%
-- Taxes on Income 4413 5290 2504 2786 21.0% 19.9% 16.4% 23.2%
-- Less Share of States 6730 7881 4320 3561 10.7% 17.1% 12.1% 23.8%
(b) Non-tax Revenue 2360 2451 1386 1065 -13.5% 3.9% 31.4% -49.5%
II. Capital Receipts (ex-borrowings) 1175 922 263 659 79.7% -21.5% -57.5% 96.0%
III. Total Expenditure 22178 24422 16132 8290 12.3% 10.1% 9.1% 12.2%
-a Capital expenditure 2734 3004 1914 1090 -3.9% 9.9% 4.0% 22.0%
-b Revenue expenditure 19443 21418 14218 7200 15.0% 10.2% 9.8% 10.8%
--interest 5308 5760 3482 2277 10.4% 8.5% 12.4% 3.0%
--subsidy 2641 2928 2190 738 12.5% 10.9% 1.2% 54.9%
IV. Fiscal Deficit (III-I-II) 5948 6243 7166 -923 11.1% 4.9% 17.1% 435.2%
GST revenue likely
to fall short of BE
Direct tax can
surprise on upside
Interim dividend
from RBI to provide
further support
Expenditure growth
could be cut back
marginally to reduce
fiscal slippage
Source: Budget Documents, Economic Survey, CEIC, Morgan Stanley Research
E = Morgan Stanley Research estimates
51

January 29, 2019 03:01 AM GMT
India Equity Strategy | Asia Pacific
QE Dec-18 Earnings So Far
Early indicators suggest that aggregate earnings are a tad
ahead of Morgan Stanley analyst expectations, although stock
price reactions have been subpar.
One-fourth of Morgan Stanley's Indian coverage has reported earnings so far:
Revenue, EBITDA, and net profit growth stand at 31%, 16%, and 9% YoY, with
revenue growth beating strongly and in-line net profit growth. YoY margin
compression is 257bps. Ex-energy, revenue, EBITDA, and net profit growth stand
at 18%, 14%, and 9% YoY, with a beat of 3ppt on revenue growth and a 1ppt miss
on net profit growth. YoY margin compression is 73bps.
The earnings beat ratio stands at 54%, while relative stock performance (the
proportion of Morgan Stanley coverage stocks that outperformed the Sensex a
day before and after the results) has slipped to 43%. In sectors where three or
more companies have reported earnings, the breadth of earnings beats was
greatest in Communication Services (at 100%), Materials (at 87%) and NBFCs (at
80%). However, in the case of NBFCs, no stocks have outperformed after results,
whereas in the Communications and Materials sectors, only a third of the stocks
have outperformed the index since results.
So far, the revenue growth beat has been broad-based with not a single sector
missing revenue growth estimates. At the net profit growth level, there are
marginal misses across sectors with the exception being Communication Services.
Twelve Sensex companies have reported revenue, EBITDA, and net profit growth
of 33%, 17% and 9% YoY. Net profit growth is 0.2ppt ahead of our analysts'
expectations. For the 17 Nifty companies, revenue, EBITDA, and net profit growth
of 31%, 17% and 10% YoY; Here the net profit growth is 1.3ppt ahead of our
analysts' expectations.
Broad market trends: About 334 companies (~8% of the sample) in the broad
market have reported revenue and net profit growth, registering 33% and 7%
YoY with margin compression of 254bps.
Earnings growth forecast revisions: Since the start of the earnings season,
consensus for Sensex EPS growth is up 7bps for F19 but down 136bps for F20.
Stock-level earnings estimate revisions: Since the start of the earnings season,
Morgan Stanley analysts have lowered F19 earnings forecasts for 37% (13) of
covered companies following earnings release (based on estimate revision data
available for 18 companies up to 28 January). Consensus for eight of these
companies has declined more than 2%. The increase in F19 estimates for all five
companies for which estimates have risen has been 2% or more. See Exhibit 7
Consensus F19 earnings estimates have dropped for 46% (16) of companies
covered by Morgan Stanley since earnings release (based on estimate revision
data available for 35 companies up to 25 January). See Exhibit 3.
MORGAN STANLEY INDIA COMPANY PRIVATE LIMITED+
Sheela Rathi
EQUITY STRATEGIST
Sheela.Rathi@morganstanley.com
Ridham Desai
EQUITY STRATEGIST
Ridham.Desai@morganstanley.com
+91 22 6118-2224
+91 22 6118-2222
Morgan Stanley appreciates your support in
the 2019 Institutional Investor All-Asia
Research Team Survey. Voting will open mid-
February 2019.
Exhibit 1: Earnings Trajectory for the Last Few
Quarters
YoY Revenue growth Q3F18 Q4F18 Q1F19 Q2F19 Q3F19E Q3F19E* Q3F19A*
MS coverage 15% 14% 22% 21% 9% 19% 31%
MS coverage ex-energy 12% 11% 17% 12% 10% 15% 18%
Broad Market (1178 companies) 13% 12% 17% 20%
Broad Market ex- energy 12% 12% 13% 13%
BSE Sensex 12% 16% 22% 15% 13% 19% 33%
Nifty 50 14% 16% 23% 22% 8% 18% 31%
YoY Earnings growth Q3F18 Q4F18 Q1F19 Q2F19 Q3F19E Q3F19E* Q3F19A*
MS coverage 8% -33% 7% 21% 9% 9% 9%
MS coverage ex-energy 3% -44% -3% 12% 28% 10% 9%
Broad Market (1178 companies) -4% -44% 8% 1%
Broad Market ex-energy -7% -49% 0% -2%
BSE Sensex 4% -18% -5% 15% 21% 9% 9%
Nifty 50 6% -16% 4% 22% 2% 9% 10%
*Morgan Stanley analyst estimates for the 35 companies that have reported thus
far. Source: Company data, Capitaline, Morgan Stanley Research
Morgan Stanley does and seeks to do business with
companies covered in Morgan Stanley Research. As a
result, investors should be aware that the firm may have a
conflict of interest that could affect the objectivity of
Morgan Stanley Research. Investors should consider
Morgan Stanley Research as only a single factor in making
their investment decision.
For analyst certification and other important disclosures,
refer to the Disclosure Section, located at the end of this
report.
+= Analysts employed by non-U.S. affiliates are not registered with
FINRA, may not be associated persons of the member and may not
be subject to NASD/NYSE restrictions on communications with a
subject company, public appearances and trading securities held by
a research analyst account.
1

QE Dec-18 Earnings Season Tracker
Exhibit 2: Morgan Stanley's Coverage in India – Earnings Season Trends
Source: Morgan Stanley estimates, Bloomberg estimates, company data, Capitaline, Morgan Stanley Research
2

Exhibit 3: Consensus earnings estimate revisions since results
Company Name
Earnings Revision
(F19)
Earnings Revision
(F20)
Just Dial 4.9% 0.5%
Zee Ent. 3.0% 0.6%
HDFC Bank 2.4% 4.8%
Bharti Infratel 2.3% 2.9%
Biocon Ltd 2.2% 0.8%
Yes bank -2.1% -1.2%
Reliance Industries -2.5% -2.7%
United Spirits -2.5% -2.5%
TVS Motors -2.7% -1.2%
AU Small Fin Bank -3.9% -5.7%
Infotech Ent. -5.2% -4.6%
IndusInd Bank -5.4% -1.4%
Interglobe Aviation -68.6% 11.7%
Source: RIMES, IBES, Morgan Stanley Research; Note: Companies with revisions above / below + / - 2% for F19 respectively
3

Exhibit 4: Number of Companies Beating Morgan Stanley Analysts' Estimates
Number of companies beating MS analyst estimates
MS Coverage 3QF19 2QF19 1QF19 4QF18 3QF18 2QF18 1QF18
Cons. Disc. 50% 47% 25% 13% 40% 73% 47%
Cons. Staples 25% 60% 60% 50% 80% 56% 11%
Energy 100% 25% 63% 13% 25% 38% 33%
Financials 42% 52% 69% 48% 48% 40% 34%
Healthcare 100% 33% 50% 25% 33% 92% 40%
Industrials 67% 36% 67% 45% 73% 36% 36%
Materials 67% 33% 67% 67% 62% 57% 87%
Technology 50% 80% 50% 75% 92% 92% 75%
Comm. Services 100% 50% 67% 33% 33% 33% 67%
MS Coverage 54% 37% 57% 42% 53% 58% 48%
Source: Company data, Morgan Stanley Research
4

Exhibit 5: Number of Companies Outperforming Sensex after Results
Number of companies Outperforming Sensex post results
MS Coverage 3QF19 2QF19 1QF19 4QF18 3QF18 2QF18 1QF18
Cons. Disc. 50% 40% 18% 33% 33% 60% 53%
Cons. Staples 0% 40% 40% 60% 40% 56% 44%
Energy 100% 38% 25% 50% 50% 25% 67%
Financials 33% 64% 39% 65% 42% 47% 55%
Healthcare 0% 42% 42% 58% 58% 42% 40%
Industrials 100% 64% 33% 36% 55% 18% 36%
Materials 33% 27% 40% 27% 54% 50% 53%
Technology 67% 30% 33% 33% 50% 42% 42%
Comm. Services 33% 50% 33% 67% 33% 100% 100%
MS Coverage 43% 47% 36% 48% 47% 46% 51%
Source: RIMES, Morgan Stanley Research
5

What Index Funds Can't Do
Jack Bogle died yesterday... I hardly need to tell you about him. As Warren
Buffett wrote in his 2017 annual letter: “If a statue is ever erected to honor the
person who has done the most for American investors, the hands-down choice
should be Jack Bogle.”
But today we ask, how to beat the monster he created? One answer lies in
honing in on the one thing index funds can't do...
When I think about the future of money management, I still see
index funds with a huge slug of the pie.
But what about the rest of it? What do the “survivors” look like?
Well, I think the survivors will offer something that is markedly
different than what you get in an index fund. One species of
survivor will be the concentrated investors.
For the sake of discussion, let’s say concentrated means
portfolios with no more than 20 securities. The idea is you don’t
bet much, but when you bet, you bet big. This is far from how
most people manage money.
Anecdotally, there are many compelling case studies that say this
is the way to go. I’d recommend Concentrated Investing: Strategies of
the World’s Greatest Concentrated Investors by Allen Benello, Michael van
Biema and Tobias Carlisle. There are some wonderful stories in
there.
For example, Lou Simpson ran GEICO’s portfolio from 1979 to
2010. His record is extraordinary: 20% annually, compared to
13.5% for the market.
Simpson’s seemed to get more concentrated over time. In 1982,
he had 33 stocks in a $280 million portfolio. He kept cutting back
the number of stocks he owned, even as the size of his portfolio
grew. By 1995, he had just ten stocks in a $1.1 billion portfolio.
A lesser-known example is Joe Rosenfeld at Grinnell College. The
endowment had $11 million in assets when he took the helm in
1968. When he stepped down in 1999, it was up to $1 billion.
Rosenfeld had delivered 15% annually – net of the 4.75% that
went to the college every year. Astounding, really.
He did it by buying a handful of stocks and holding on. In 30
years, he made half a dozen major investments and sold even
more rarely. Rosenfeld “considers selling to be indistinguishable
from error.”
Of course, this approach led to some harrowing moments. In
1990, the endowment dropped a third, thanks to a giant position

in Freddie Mac. But Rosenfeld held on. (I don’t know what this did
to his insides.)
Okay, so there are lots of anecdotes. What about empirical
research?
Here is a survey of some of that research by Lazard Asset
Management. They say most research supports concentrated
investing but “the empirical results… are not unanimous.”
I’m not sure there is a right answer. My gut says that your
success with a concentrated portfolio probably depends more on
temperament than anything else. Concentrated portfolios tend to
be more volatile. And if you can’t stomach the ups and downs, it
probably won’t work for you.
But it also begs another question…
How concentrated is concentrated?
Number of positions is one thing. But that’s not the only
dimension here. How big do you let positions get? Because if you
buy and hold and you nab a big winner, then you may well get a
nutty looking portfolio after some years.
Say you took a 3% position in Intel in 1987 and never sold.
Twenty years later, it would pretty much be your entire portfolio.
Of course, almost nobody would allow this to happen.
Remember how last week I wrote about Stahl’s essays? In 2017
he wrote an essay titled “How Could Indexation Ever Be
Invalidated?” (I took the Intel example from this, though I
could’ve chosen lots of other examples). To answer his question,
I pose another question:
What is one thing an index can’t do?
An index can’t take a 3% position in an Intel and let it become a
bigger and bigger piece of the portfolio.
Aha. Maybe here, then, is a chink in the armor where an active
manager can thrust his sword. An index must always rebalance.
In essence, it must always sell its winners and add to its losers.
But you do not.
Stahl concludes:
“If the only assertion about indexation is that the index will
outperform the active managers, then the only way to invalidate
indexation is to outperform the index. The index can be made to do
anything except compound into heavy concentration. This is an approach
that the active manager might do well to explore.” [Italics
added].
I’ve been running concentrated portfolios my whole investing life.
I’m sold.

But not everybody is. I spoke with one guy who told me letting a
position get to 20% of the portfolio would be “financially
irresponsible.”
Would it? What if it started out as a 3% position?
This is the conundrum of money management today. Everybody
seems to be watching the S&P500 Index. They want you to beat
that index. But to beat that index means you have to do things
the index doesn't. One way to do that is to allow your portfolio to
become… top heavy, chunky, unbalanced – choose your
adjective.
But not many people want to do that, because it means suffering
more volatility. And everybody seems to want low volatility. But
for those who can do something at variance with the index, I
believe there are big rewards.
For myself, I like to start no bigger than 10%. I would not let a
position grow to more than 20% of the portfolio. And it would
have to be a very special position to get that big. Even those who
like concentrated bets have limits. As well they should. You’re
going to make mistakes. You don’t want to die from one mistake.
This reminds me of a Nick Murray quote, from his wise little book
Simple Wealth, Inevitable Wealth: “The fewer ideas in your portfolio, the
fewer bullets it will take to kill you. One idea: one bullet.” (Murray is
not a fan of stock picking, by the way. He’s an asset allocation
and index sort of guy. Well, nobody’s perfect).
I run a concentrated portfolio, but try to take a balance of risks. I
own companies in different industries and that do business in
different places all over the world. I’m mindful of that one bullet.
Of course, not every position starts at 10%, but I hesitate to
keep anything less than a 3% position around for too long. Raise
or fold, as they say in poker. Again, the precise numbers are
more a personal choice. This is not a science. It is more an art.
Moreover, such positions must meet my CODE investment
criteria. This means, among other things, a very strong balance
sheet. Perhaps this goes without saying, but certain styles are
better suited to concentrated portfolios than others. For example,
those who invest in small biotech firms or junior miners probably
should spread their bets.
The Secret to Success? Tennis Shoes!
I’ll end this bit on concentrated investing with a funny story Glenn
Greenberg, founder of Brave Warrior, tells. This story is in
Concentrated Investing. Greenberg worked for a family office. The
money manager there was a guy named Arthur Ross:

“Nobody’s ever heard of him because he handled private money
and he didn’t get written up in books or get quoted in the
newspapers, but he was a really phenomenal investor.”
One of the family members came into Ross’s office one day and
asked, “Arthur, what’s the secret of your success?”
Ross said, “Tennis shoes. Now get out of my office.”
And the guy leaves and thinks to himself, “Tennis shoes? I don’t
get it.” So he goes down the hall to the office of one of Ross’s
analysts, and said, “Arthur told me the secret to his success is
tennis shoes.”
The analyst tells him that Ross meant ten issues. He owns ten
issues. Just ten stocks.
Maybe people are starting to figure this out. An article from the
Economist earlier this year cited data showing the average
number of stocks in global portfolios halved over the past decade.
*** Mailbag
A reader writes:
“Maybe I misunderstand coffee can approach but a few concepts
seem to have burrowed down into my mind and wont leave me
alone when it comes to making investment decisions. One is
courtesy of Danny Kahneman and his ‘base rate’. When asked a
difficult question he says you need to ask yourself what the
relevant base rate is before answering. So, in this case, buying a
small number of stocks and holding for a very long time…is that a
good idea? Tom Gaynor of Markel gives folksy stories about his
granny not selling her husbands stocks and lo and behold they
were worth a small lottery win when she died so the lesson is,
never sell? But, for my sins I was a bond dealer for 20 years
before retiring and so have become incredibly skeptical of all such
easy tales of great wealth. JPM did a study that came out last
year that shows since 1980s nearly all stocks outside the top
handful have delivered as a group zero returns, e.g. the right tail
accounted for nearly all market gains. Back to base rates, what
are the odds you or me picking a few tuck aways are going to
pick the (very) few that actually do deliver? Very low.”
Yes, this reminds me of a report I read four years ago, which said
much the same thing: “The Agony and the Ecstasy: The Risks and
Rewards of a Concentrated Stock Position.” It’s a good read.
The key here is to think about the population used to get at a
base rate. The odds from the population as you define it – or as
these studies define it – seem poor.

But… by applying some basic principles to sift through these
populations, the odds of putting a portfolio together that does
very well over time turns more favorable. For example, the base
rate for owner-operated firms is quite a bit better. There are
many studies that show how companies with high insider
ownership outperform their peers.
You can choose whatever factors you like, that's not the only one.
You could use price-earnings ratios or some other valuation
metric. You could use Joel Greenblatt’s Magic Formula, or Pabrai’s
Cannibals or some other sensible screen. Then you pick from that
sifted population.
The point is: within certain subsets, or mini-populations, the base
rate turns favorable.
Nonetheless, you raise an excellent point. An investor needs a
way to improve the odds. This is why good investors spend so
much time on process.

Can More Information Lead to Worse
Investment Decisions?
JANUARY 9, 2019 / JOE WIGGINS
It is without question that investors now have easy access to more
information than ever to guide decision making; optically, this surfeit of data
appears to be a positive – who doesn’t want more ‘evidence’ to inform their
judgements? Yet there are a number of potential drawbacks, most notably the
challenge of disentangling signals from a blizzard of noise in order to make
consistent decisions. For this post, I want to specifically address the potential
consequences of information growth and its impact on our precision and
confidence levels. Whilst we often believe that more information can improve
our accuracy (the number of correct decisions we make), in certain situations
all it may be doing is increasing our (unfounded) confidence.
More information does not necessarily lead to better decisions: In the
investment industry it can often feel as if it is the amount of information or
evidence that matters, rather than its validity. Provided a research report is
long enough, the conclusion must be sound. I would contend, however,
that for many investment decisions there are only a handful of information
points that are relevant, distinct, and materially impact the probability of a
positive outcome. If this is the case, why is there such a desire for more
and more information?
– We don’t know what that relevant information is, therefore we include
everything we can find.
– We struggle to realise that many pieces of information are telling us the
same thing.
– In random markets, noise can be mistaken for relevant information.
– If a decision goes wrong, we at least want to show that we did a lot of
research to support it.
– It is difficult to sell our investment wares if we simplify our decision
making to a select few variables.
– It we make simple decisions based on a narrow range of information we
can look lazy, inept and unsophisticated.

– We feel more comfortable / confident in a decision if it is ‘supported’ by
more evidence.
– It is possible that information that was once relevant ceases to be so
because of some ‘regime shift’.
This combination of factors (and others I have failed to mention) means
that it is incredibly difficult not to focus more on the accumulation of
information rather than seek to identify the information that matters.
More information can lead to overconfidence: It is not simply the case
that more information might not result in greater decision making accuracy,
but that it can lead to us becoming more overconfident and poorly
calibrated in our judgements. Whilst we often believe that ‘new’ information
bolsters the case supporting our choices, on many occasions this additional
evidence may simply be a repetition of prior information (merely in a
different guise) or be erroneous with no predictive power (a major problem
in an environment marked by uncertainty and randomness where things
that look like they matter, actually do not). As we receive more information,
therefore, we are prone to believe that we are more accurate in our
decisions, when there is often no justification for this. This can create an
anomalous situation where behaviour consistent with being diligent and
thorough, actually results in worse investment decisions being made.
Judging the balance between carrying out sufficient research and
becoming overly confident by collecting reams of superfluous data is
fraught with difficultly, however, all investors should think more about what
is the most relevant information, rather than concentrate simply on the
accumulation of more. For professional investors, a simple idea is to
decide which pieces of information they would use if there was a restriction
(of say only 5 or 10 items) and then monitor the outcomes of decisions
made utilising only these select variables. Such an approach forces us to
think about what evidence really matters to us, whether it is effective and
what value we might add over and above such a basic method.
—
[i] Tsai, C. I., Klayman, J., & Hastie, R. (2008). Effects of amount of
information on judgment accuracy and confidence. Organizational Behavior
and Human Decision Processes, 107(2), 97-105.

Memo to:
From:
Re:
Oaktree Clients
Howard Marks
Political Reality Meets Economic Reality
In 2016 I wrote Economic Reality (in May) and Political Reality (in August), two memos covering
subjects I thought were important and timely. In the latter, I summed up Economic Reality as follows:
[It] describes the ways in which economics defines and constrains reality in business,
investing and everyday life. Economics establishes the rules of the game and the
but not without consequences.
absolute, like the laws of physics (e.g., gravity), but they reliably establish tendencies and
limits.
The point is that the field of economics covers the choices people and organizations face; the costs,
possible rewards and potential consequences; and how decisions regarding those choices are made.
These are the bases on which people enter into economic transactions. More than anything else, perhaps,
economics is the study of choice.
Three months later, in Political Reality, I said:
phrases that are internally contradictory
world of politics has its own, altered reality, in which economic reality often seems not to
impinge. No choices need be made: candidates can promise it all. And there are no
consequences. If something might have negative consequences in the real world,
politicians seem to feel free to ignore them. . . .
The purpose of this memo is to describe what happens when political behavior collides with
economic reality, , as illustrated in one area where the government is taking steps tariffs and
another in which debate among politicians is heating up restrictions on the capitalist system.
Before I move forward, d like to state up front, as I did in Economic Reality in 2016, that I m not
writing to make political judgments or to make any politician or party look bad. But economic
pronouncements can t be separated from the people who make them. If you read through to the end,
something to complain about in the approach of members of both parties.
Tariffs
Tariffs are very much in the news these days, and their complexity renders them ripe for error and thus
appropriate for discussion here.
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

Many people albeit more often than economists in general applaud his
decision to impose tariffs against China. Whereas the simple story was that he was doing so to (a) reduce
our trade deficit with China, (b) support U.S. manufacturers and (c) protect U.S. jobs,
in
play. In The Wall Street Journal of October 20, Richard Haass, president of the Council on Foreign
Relations, an independent, nonpartisan organization, enumerated complaints that have been lodged
against China in the area of trade:
. . . higher-than-warranted tariff and non-tariff barriers, forced transfers of technology,
theft of intellectual property, government subsidies and currency manipulation designed
to make exports cheaper and to reduce the demand for imports.
Everyone knowledgeable tells me these complaints are warranted. While the new, past presidents
much about them, or at any rate
produce any results. Clearly Trump likes
to take action
confrontation. G
reliant on exports to the U.S. than ours is on exports to China and given C
economic growth in order to reach its goals imposing tariffs represents a possible way for Trump to get
China to alter its behavior.
Thus rather than criticize
use them as an example to illustrate the
central messages of this memo: (a) economic actions have costs and consequences, (b) for that
e solutions to complex problems, (c) given the
complexities, few people thoroughly understand economics, and (d) because of that understanding
deficit,
posed solutions often fail to receive the scrutiny they should.
The U.S. runs chronic trade deficits with most of its trading partners, and
with China it amounted to $335 billion in 2017. Trump takes these deficits to mean our trading partners
are .
they have ing us, suggesting something
nefarious about trade deficits. But is that the correct inference? The other day I went to the barber for a
haircut, and when I paid him, I ran a trade deficit. He got my money, and I got a haircut.
I had lost. Likewise, Chinese businesses make money from the U.S., and U.S. consumers get the lowpriced
goods they want. Both sound like winners to me.
Trump has
d we? That would be true
importing, or if we were able to buy them cheaper
domestically. Would it really save us money to not trade with China?
After all, w
the countries into which goods are imported.
exporters and presumably passed on to consumers in
e.
If tariffs are paid by consumers in the importing nations, what to be accomplished by imposing them?
In short, to raise the cost of foreign goods and thus discourage their consumption. But
that leads us to the knock-on effects: what else happens?
2
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

escalation on trade: the imposition of tariffs of 25% on
imported steel and 10% on imported aluminum. Here are some of the many possible complications,
ramifications and second-order consequences:
Tariffs on imported intermediate goods such as steel and aluminum might increase the cost of
finished goods manufactured in the U.S., rendering them less competitive if their prices are raised
(or less prof ). According to The New York Times of July 4, 2018:
The Aluminum Association, which represents the bulk of the American industry,
says that 97 percent of American jobs in aluminum are at what are called
hape the metal into things like auto parts and other
pay higher prices for their raw materials.
To avoid paying tariffs, American manufacturers could reduce their imports of foreign steel and
aluminum for use in the finished goods they make, and instead increase their imports of finished
goods which are not subject to the tariffs made abroad with foreign steel and aluminum.
Going beyond importing finished goods, American companies could move their manufacturing
overseas, cutting domestic jobs. The overseas use of untaxed, low-cost metals could provide a
competitive edge when those finished goods are imported into the U.S.
Non-U.S. companies likewise could gain an advantage over their American competitors. Their
use of untaxed, low-cost materials could give them lower selling prices or higher profit margins
when exporting finished goods to the U.S.
Despite the cost increases caused by tariffs, imports might not actually be discouraged and U.S.
:
said Eric Krepps, who runs
the North American automotive business at Constellium NV, a Dutch aluminum
. . . since the U.S. produces just 13% of the 5.6 million metric tons of raw aluminum
it uses each year. (The Wall Street Journal, July 18, 2018)
Since tariffs might raise selling prices on imported goods (or goods incorporating imported
materials and components), the reduced competitiveness of those imports could enable domestic
producers to raise their prices. The result would be higher consumer prices on all brands.
Countries whose goods are subjected to tariff increases are unlikely to just sit there and take it.
Retaliation is always a reasonable expectation.
the potential to hurt thousands of others. Businesses that depend on access to overseas markets
are being hit with retaliatory tariffs . The New York Times, August 7, 2018)
Finally, a trade war centered on escalating tariffs makes the global environment less stable,
reducing predictability and
3
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

Going beyond steel and aluminum, increased tariffs on imported automobiles and auto components have
been under discussion for much of the past year. Some of the considerations described above regarding
apply
finished goods, not intermediate goods. But a
number of additional elements create exceptional complexity:
U.S. companies manufacture cars in the U.S. for sale abroad.
U.S. companies manufacture cars abroad for import to the U.S.
Some of the biggest manufacturers of cars in the U.S. are non-U.S. companies.
Many of the cars produced in the U.S. by non-U.S. companies are destined for export.
Cars made in the U.S. incorporate a lot of components made elsewhere.
Of the cars sold in the U.S. last year, 44% were imported.
On July 20, The New York Times discussed the possibility of increased tariffs on autos as follows:
If imposed, the tariffs would most likely have deeper and wider-reaching repercussions
with one work force
in a supply chain that can snake through small American towns and cross oceans.
Thus increased tariffs on automotive imports could bring about:
an increase in the price of all cars bought by Americans,
a resultant decline in the number of cars sold,
tougher times for manufacturers, dealers, support businesses and their employees, and
thus a general contraction of the economy.
tariffs would reduce global economic output by $430 billion, or half a percent, in 2020, if they
remained in place and shook consumer
(The New York Times, July 23, 2018))
The bottom line is that t simple solution or a
with
potential benefits, but also costs and risks. They can help some parts of the economy and
simultaneously
One study of the Obama tire tariffs found in a single year, 2011, Americans spent an
extra $1.1 billion on tires as a result of a tariff that preserved, at most, 1,200 jobs. That is
almost $1 million per job, for jobs paying an average of about $40,000.
Steel tariffs imposed in 2002 by President George W. Bush yielded similar results,
penalizing not just consumers but companies that use steel to make other products, like
construction companies and carmakers. The Dartmouth economist Douglas Irwin
estimated 140,000 American workers make steel, while 6.5 million workers make
products that include steel.
New York Times, September 17, 2018)
If you care about
4
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:
The

move to wrap up on the subject of tariffs with a few paragraphs from Economic Reality:
Have the vo
goods manufactured at U.S. wages or tariffs designed to bring the cost of Chinese
goods up to those levels
How will the
interests of the 3.2 million Americans estimated to have lost their manufacturing
jobs to China be balanced against the hundreds of millions who would have to pay
considerably more for imported goods? Not an easy question.
example of ways in which policy decisions can lead to distortions. Since the industries
for which tariffs and subsidies are established are, by definition, industries that
decision that (a) these industries should be kept afloat and (b) consumers of these
prevail if consumers had easy access to goods from abroad, free of tariffs. . . .
laws
explanation, the main reason the U.S. has lost manufacturing jobs to foreign countries is
that people there are willing to work for much less. In this globalized world, that
-paying manufacturing jobs they used to
have and the low-
On two occasions last summer, while discussing the steel and aluminum tariffs, The Wall Street Journal
did a good job of summing up the key considerations:
The fallout, while so far limited, illustrates how efforts to protect some companies can
cause unintended pain for others. (June 4, 2018)
Put into practice, tariffs are a complex economic weapon that can ricochet through an
, 2018)
As mentioned earlier,
(or administrations that impose them), but
rather to show (a)
actions to improve the functioning of economies and (b)
there are ramifications to be considered. Tariffs are typical of economic reality, and economic reality is
complex, in large part because it consists mainly of dividing resources among participants, not of creating
more for everyone.
Anti-Capitalism
Something else is going on that I worry about far more than the imposition of tariffs: increasing
anti-capitalist sentiment.
5
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

One of the big trends in politics in recent years has been the rise of populism. While populism is
somewhat amorphous, h
A political philosophy supporting the rights and power of the people in their struggle
against the privileged elite. (The Free Dictionary)
to add another word with regard to the adoption of populism as a political strategy: it
plays on resentment on the part of the people toward the elite.
Populism has been on the rise in Europe for a number of years, generally associated with the political
right and characterized by resentment toward economic, liberal and urban elites. It has often been
accompanied by authoritarianism, allowing charismatic strongmen to present themselves as protecting
like immigration.
A good part of the credit for Donald
likewise been attributed to populism.
This instance, also coming from the right, was largely built on resentment from rural, white, older and
less-educated voters directed at urban, establishment, educated and cultural elites, as well as unhappiness
with social and demographic trends that are disrupting the status quo.
But as shown in the 2016 presidential Democratic primary contests and since, another wave of populism
has arisen from the left. I
in this case, the principal
targets of popular
resentment are capitalism and capitalists.
One of the big stories of the 2016 primary season was the success of avowed Democratic Socialist
Senator Bernie Sanders. Sanders launched a challenge to Hillary Clinton, the heir-apparent to the
leadership of the Democratic Party and eventually the chosen nominee. He gained a lot of followers and
gave Clinton a run for her money, in particular by emphasizing economic justice, the corrosive effect of
money (and especially corporate money) in politics, and the promise of healthcare and education for all.
he so-
left wing of the Democratic Party is
becoming a formidable bloc. I expect progressives to be a force to be reckoned with in the coming
years. They will show up strongly in the 2020 primaries and influence the debate. In fact, their
influence is already being seen. And thus this section of my memo.
In a possibly isolated but telling incident, in a Democratic congressional primary last year in Queens,
New York, Alexandria Ocasio-Cortez came from the far left to beat Joe Crowley, a ten-term, center/left
congressman. Crowley was #4 in the Democratic leadership in the House of Representatives and
considered a likely eventual successor to Nancy Pelosi as House Speaker. Instead he was ousted by
Ocasio-Cortez: 28 years old at the time and sporting a storybook bio featuring a working-class
upbringing, academic distinction and stints as a bartender and waitress. She had been politically oriented
but had never held elected office. And yet she became the youngest woman ever elected to Congress.
She s been very outspoken since and has attracted disproportionate attention for a freshman legislator.
Ocasio-Cortez, like Sanders, is a member of the Democratic Socialists of America, and she willingly
accepts the label
New Yorker
I do think we are in a crisis of late-stage capitalism, where people are working sixty,
018)
6
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

Julia Salazar, another member of the D.S.A., also ousted a Democratic incumbent last year and won
election to the New York State Senate -Cortez The same article
included a statement from her that I found chilling:
oppressive, and is actively working to dismantle it and to empower the working class and
Does this group genuinely want to abolish capitalism? Thankfully, the same article went on to reflect
some moderate sentiment:
Michael Kazin, a co-editor of Dissent
major influence in American history is to push liberals, progressives, to the left. And that
of America in my lifetime.
In July, The New York Times
as follows:
Security and Amtrak. The D.S.A. itself both embraces and rejects such friendly
of exploitation. . . .
(home to robust maternity leave and universal health care) or even to lost relics of
t in human
welfare). (July 22, 2018)
Ocasio-Cortez and Salazar may not be indicative of a broad movement, as they hail from New York City,
where a Democratic candidate is a sure thing in a general election and extremism is unlikely to be an
impediment. But some trends among our citizens are very much worth noting. According to the New
Yorker article cited above:
ages of eighteen and twenty-nine, and discovered that support for capitalism was
surprisingly low. Fifty-one percent of the cohort rejected capitalism; thirty-three percent
supported socialism. A later edition of the survey found that fifty-one percent were
ercent were hopeful. . . .
Seventy-eight percent of Americans working full time live paycheck to paycheck; nearly
half do not have four hundred dollars at the ready. . . .
7
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

. . .while ninety percent of people born in the nineteen-forties outearned their parents
the traditional American expectation this number has fallen to fifty percent for people
born in the nineteen-eighties. [Of course, they could be too young to have done so yet.]
These are the dystopic trends Ocasio-Cortez cites and the source of the resentment of capitalism that gives
As I see it, for the 60 years immediately following World War II, much of the world enjoyed a rising tide
of prosperity that lifted all boats. That made nearly everyone economically content and thus happy with
capitalism and free-market solutions. Even though some people did better than others, most did quite
well. Living standards rose and the incidence of poverty declined. Ronald Reagan and Margaret
Thatcher celebrated the efficacy of free markets, and the world agreed.
Now the rate of economic progress has receded and current trends are less cheering:
1. The possibility that economic growth will be slower than that of the post-war period
2. The negative impact of globalism and automation on specific groups
3. The increased importance of advanced education or the ownership of capital
4. As a consequence of numbers 2 and 3 above, increased income inequality
In short, the tide is no longer rising to the same extent, and many fewer people are happy with their
circumstances and outlook. Their unhappiness crystalizes in populism. And it needs a target. Why
not capitalism?
My point here is that, as I said above, I expect the rising influence of the left to impact the 2020 election
cycle. Left-wing Democratic candidates will present challenges to moderates in their party, and the latter
In particular, I cite two pieces of
proposed legislation that emerged recently from prominent Democrats:
Senator Elizabeth Warren, already an announced 2020 presidential candidate, has introduced her
Accountable Capitalism Act. Two of its provisions caught my attention:
. . . incorporation for large companies would become a federal matter, . . . These
federally chartered companies would be mandated to consider the interests of a list
of stakeholders, from investors to employees to customers and communities. These
groups could then sue if they deemed the company had breached their duties. . . .
percent of directors to be elected by
employees. (The Financial Times, September 24, 2018)
Senator Cory Booker of New Jersey, often mentioned as a presidential hopeful, has introduced
legislation that I view as related:
The Worker Dividend Act would mandate that companies buying their own shares
must also pay out to their own employees a sum equal to the lesser of either the total
value of the buyback or 50 percent of all profits beyond $250 million. (Vox, January
10, 2019)
8
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

I absolutely am not writing to defend stock buybacks or criticize labor representation on boards.
What I oppose is (a) the idea of governments deciding how companies will be run and (b) the
What would be the effects of turning over some of businesses capital to workers, or requiring that they
be put on corporate boards? Clearly, to do the former would be comparable to saying to shareholders,
thought you owned the company
way of returning
each one be accompanied by giving an
equivalent am
a company pays a dividend,
it has to distribute an equal amount to its
tantamount
for corporate capital
yourself who would start a
corporation in the future if it meant the workers would be entitled to half the gains.
What about requiring that workers be put on boards? To date, it has been the job of a corporat
directors to represent its shareholders. Requiring that 40% of them be workers would be, in essence,
another way of saying the shareholders
in full control. If workers were put on boards, whose
interests would they represent: the corporation and its shareholders, or labor? To whom would they work
to deliver benefits? If an opportunity arose to increase efficiency and profitability by investing in
automation, for example, how would labor be expected to vote?
And that leads to the matter of requiring corporations to serve multiple interests. Today, directors are
legally deemed to have done their jobs if they applied
(and thus its shareholders). How would they be expected to simultaneously work for the good of the
company and its owners as well as its workers, customers and communities? Can you imagine the
lawsuits that would fly over the issue of whether too much had gone to one group rather than
another? How could a court decide whether the multiple constituencies had benefitted in the
appropriate proportions?
to do is get some of the progressive politicians and the less-capitalist young people in a
room and ask them a simple question: To
over the last hundred years and the generally superior living standards of its people? In short,
w
r, more
rigid
social and financial structures. But, extremely importantly, I also think there have been enormous
contributions from capitalism/free enterprise, the free-market system, economic incentives, private
ownership of property, individual economic opportunity, and the very limited involvement of
government in the economy.
Capitalism is an imperfect economic system, because differential performance in the pursuit of economic
success as well as luck results in there being (a) some people who are less successful as well as some
who are more and (b) a few who are glaringly successful.
someone who has profited from
capitalism, so my views could be dismissed as hopelessly biased.
the
capitalist system has produced the most aggregate gains for our society, exceptional overall progress, and
a better life for most. For me, the best assessment of capitalism is the one Winston Churchill applied to
democracy:
9
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

No one pretends that democracy is perfect or all-wise. Indeed, it has been said that
democracy is the worst form of Government except all those other forms that have been
tried from time to time.
In the same way,
is the worst economic system . . . except for all the
rest. No other economy has accomplished what the U.S. has, accompanied by extensive personal
freedom, and especially not the ones centrally controlled by government. In particular, no other economy
has produced inventions and innovations and distributed life-enhancing products like the U.S. has.
in favor of unfettered behavior on the part of corporations.
behave in anti-social ways, or do damage in pursuit of profit. Thus laws, regulations and active
supervision on the part of diligent directors are needed to police corporate behavior. I also think the
leaders of society should encourage companies to operate with a conscience and voluntarily work for the
betterment of their communities. But this must be done within the framework of the elements that
made America great not by subverting them.
Also, I feel
governments create effective safety nets to assist the less-fortunate
members of society who end up at the bottom of the income distribution. Capitalism can make
countries successful through the operation of economic incentives and healthy competition, but
not in favor of unmitigated dog eat
Progressives and Democratic Socialists promise increased equality of income and improvement for
people below the top. These are worthy goals, and I support them. But trying to achieve them by
dismantling capitalism would be worse for just about everyone. There is no proof that restrictions on
capitalism and government involvement in economies can promote equality other than by shrinking the
pie. Consider what it would be like if the U.S.
the sanctity of private ownership, the
efficiency of privately run business, and the incentive of personal economic advancement. The hard-
left thinks government can do things better than free markets and increase wellbeing. Which government
agencies would you like to see managing our economic engine?
A
based on closing the income gap, not just by making things better
for people at the bottom, but also by pulling down people at the top.
Thus on the TV show 60 Minutes, Ocasio-Cortez expressed fondness for a top federal income tax
rate of up to 70% on incomes over $10 million. Combined with the top New York State and City
rates, for example, that would give government 83% of the marginal income of people in the top
bracket.
terribly far from the suggestion from Jean-Luc Mélenchon, the Communist
candidate for president of France in 2017, of a 100% tax rate on incomes above
or 20 times France s average wage.)
Not dissimilarly, in November members of the House considered adjusting its rules to require a
60% super-majority to increase income taxes on the bottom 80% of Americans, but only a simple
majority to raise taxes on the top 20%. Is it fair for government to employ different sets of rules
when deciding how different groups will be taxed?
On January 24, just under the wire for inclusion in this memo, Elizabeth Warren took the issue of
differential taxation to its ultimate
s on Twitter speak for
themselves:
10
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

The rich & powerful run Washington.
that accumulated wealth.
one benefit they wrote for themselves:
t pay taxes on
We need structural change. ng something brand new an
annual tax on the wealth of the richest Americans. -
Millionaire Tax & it applies to that tippy top 0.1% those with a net worth of over
$50M.
Any populist appeal to resentment there?
And what exactly is the benefit that the & powerful . . . ? That they
get to keep what they earn net of taxes. Senator Warren omits to mention that under the
American system, nobody pays tax on accumulated wealth. But she sure makes it sound
egregious that the rich . arrange an exemption for themselves; there
is no wealth tax. But why let facts like those get in the way of political rhetoric?
Over the centuries, one thing that has brought successful democracies to an end has been the
realization on the part of the majority that they can appropriate more for themselves by taxing
those at the top. This is an example of the so-called tyranny of the majority. As The New York Times
said the other day, albeit in direct reference to Brexit:
During debates over the American Constitution, James Madison warned in one of the
essays that became the Federalist Papers that unbridled majoritarianism had made earlier
. . . as Mr. Madison warned in the Federalist Papers, a democracy im
(January 22, 2019)
Does the left understand the long-term consequences of the majority imposing confiscatory taxes on the
rich, and do they really want them? Will reducing the incentive to earn more (or incentivizing successful
Americans to transfer their citizenship to other nations) really result in the betterment of most people?
Americans generally accept the concept of progressive tax rates. But they must not be punitive and
de-motivating. Note in this regard that in 2015, the top 5% of taxpayers (with 37% of all income) paid
60% of all income taxes, and the top 1% (with 21% of income) paid 39%. To the political left: are those
proportions of taxes paid
still be fair if they were much higher?
(I want to make clear that I believe room does exist for increases in tax rates on the biggest earners since
6-year history of the U.S. income tax and (b)
dividends and capital gains are taxed at rates that are far lower still. It could be argued that all forms of
income should be taxed the same.)
While there are ways in which the system can be improved, I consider it problematic when people
denounce capitalism without acknowledging its benefits. It s ironic to think of politicians criticizing the
11
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

capitalist system via platforms like Twitter and Facebook (accessed on their iPhones); at rallies reached
via airlines and cars (perhaps employing ride-sharing services such as Uber); in meetings over a
Starbucks coffee; and via cable news networks. All of these are innovations that came out of a system
that encourages people to take significant risks to start companies on the premise that they ll reap the
rewards of ownership if their businesses succeed.
I'm sure if they thought about it, the list of innovations these people wouldn t want to live without
ranging from drugs to consumer products, to services, to technology would be a long one. Which of
those would we have today if not for the profit motive and the possibility of ending up with accumulated
wealth? And in the absence of those expectations, to whom would we look for the innovations of the
future? How the record of non-capitalist countries such as the U.S.S.R., Cuba and Venezuela in this
regard?
A great deal of America economic progress has resulted from make more
and
as
many at the top to resent. But without the contributions of those who aim for the top, everyone will
have less to enjoy (see the appendix for an informative parable). This is why I worry about the rise
of negative sentiment toward capitalism and antipathy toward those who succeed under it.
* * *
Politicians, depending on their ideology, can pose simple questions that suggest simple solutions to the
problems people face, like these:
Should we impose tariffs on imports to save American jobs?
Should workers have a say in how companies are run?
Should we enact rent control laws to protect tenants from rent increases?
Should the government provide jobs for all?
For many people, easy yes. The benefits from doing these things are obvious. Who
would oppose them?
But it turns out they
that just might exceed their upsides:
, since economic reality shows them all to have downsides
Should we impose tariffs on imports in order to save American jobs?
Do the potential gains for a limited number of workers warrant the broadly shared
increase in costs to all consumers?
Should workers have a say in how companies are run?
Will they act in the interests of the companies, society as a whole, or only labor?
Should we enact rent control laws to protect tenants from rent increases?
If rents are regulated, will landlords maintain and expand the stock of rental housing?
12
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

Should the government assure every citizen a job?
What incentive will people have to work hard if they employment?
One of the key elements running through economics is its complexity: there are few decisions that face us
- and third-order consequences. Thus w
take actions like imposing tariffs just because they offer potential benefits, without considering
their costs. And we should condemn things like capitalism solely because they
without taking into account their benefits.
Because economics is just about dollars and consumption, the belief is encouraged that it can be
understood intuitively. The truth, however, is that few people are educated regarding economics, and its
complexity and ramifications render it far less easy to understand than many people may believe. Yet,
while this stuff is complicated, we can all benefit by applying some
an economist to recognize that if you raise the prices of inputs, it increases the cost of goods and reduces
the quantity sold, and if you reduce the rewards for success
effort to create value.
The bottom line is that politicians are able to offer simple economic solutions that have considerable
appeal but fail to hold up in real life. Since politics is largely about how costs and benefits are
distributed rather than about increasing aggregate benefits
whole.
January 30, 2019
P.s.: Just prior to publication (I can hardly keep up with the developments
in this area!) I received a mass
email from a candidate for Public Advocate, public stating the
following:
. . . we
enough to support a family in this city. So we need to keep fighting. . . . A $30
minimum wage, adjusted with inflation, for New York City government workers and
businesses that employ over 75 New Yorkers would be where we start.
This brings to mind the description Winston Churchill used
regarding the folly of a nation trying to tax its
13
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

Appendix: The Tax System Explained in Beer
Suppose that every day, ten men go out for beer, and the bill for all ten comes to $100. If they paid their
bill the way we pay our taxes (by taxpayer decile), it would go something like this:
The first four men (the poorest) would pay nothing.
The fifth would pay $1.
The sixth would pay $3.
The seventh would pay $7.
The eighth would pay $12.
The ninth would pay $18.
The tenth man (the richest) would pay $59.
The ten men drank in the bar every day and seemed quite happy with the arrangement, until one day, the
owner threw them a curve ball.
cost of your daily beer by $20. Drinks for the ten men would now cost just $80.
The group still wanted to pay their bill the way we pay our taxes. So the first four men were unaffected.
They would still drink for free. But what about the other six? How could they divide up the $20 windfall
so that everyone would get his fair share?
ll by a higher percentage the poorer
he was, to follow the principle of the tax system they had been using, and he proceeded to suggest the
new lower amounts each should now pay.
And so the fifth man, like the first four, now paid nothing (a 100% saving).
The sixth now paid $2 instead of $3 (a 33% saving).
The seventh now paid $5 instead of $7 (a 29% saving).
The eighth now paid $9 instead of $12 (a 25% saving).
The ninth now paid $14 instead of $18 (a 22% saving).
The tenth now paid $50 instead of $59 (a 15% saving).
The first four continued to drink for free, and the latter six were all better off than before. But, once
outside the bar, the men began to compare their savings.
got $9
fifth man. He poin
sixth , saved nine
9 back, when I got only $2? The wealthy
14
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

The nine men surrounded the tenth and beat him up.
The next day,
w up, so the other nine sat down and had their beers without him.
But when it came time to pay the bill, they discovered something important:
money between all of them for even half of the bill!
And that is how our tax system works. The people who already pay the highest taxes will naturally get
the most benefit from a tax reduction. Tax them too much, attack them for being wealthy, and they
just may not show up anymore. In fact, they might start drinking overseas, where the atmosphere is
friendlier.
* * *
The numbers may not be exactly right, but the idea
is. The unarguable bottom line is that view of the fairness of the tax system like most
such matters depends largely on the angle from which you look at it.
HM
15
© 2019 Oaktree Capital Management, L.P. All Rights Reserved
Follow us:

Legal Information and Disclosures
This memorandum expresses the views of the author as of the date indicated and such views are subject to
change without notice. Oaktree has no duty or obligation to update the information contained herein.
Further, Oaktree makes no representation, and it should not be assumed, that past investment
performance is an indication of future results. Moreover, wherever there is the potential for profit there
is also the possibility of loss.
This memorandum is being made available for educational purposes only and should not be used for any
other purpose. The information contained herein does not constitute and should not be construed as an
offering of advisory services or an offer to sell or solicitation to buy any securities or related financial
instruments in any jurisdiction. Certain information contained herein concerning economic trends and
performance is based on or derived from information provided by independent third-party sources.
has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has
not independently verified the accuracy or completeness of such information or the assumptions on which
such information is based.
This memorandum, including the information contained herein, may not be copied, reproduced,
republished, or posted in whole or in part, in any form without the prior written consent of Oaktree.

Short Term Luck vs Long Term Skill
Daniel Kahneman, one of the fathers of behavior economics, said one of his favorite
papers was “On the Psychology of Prediction (1973).” He claims in the paper that
intuitive predictions are often unreliable because people base their predictions on
how well an event fits a story. In behavioral economics, this phenomena is called a
judgmental heuristic—representativeness, or how familiar you are personally with
the story. This is one of the worst ways to make a forecast, because it uses a highly
limited data set and allows the law of small numbers to mislead you and your
forecast. For example, one study showed that when a doctor is told that a procedure
works 50 percent of the time (essentially a coin toss probability or base rate) he or
she could get the majority of patients to undergo the procedure if he or she simply
added “The last patient who did this is doing great!” The story of success eliminates
consideration of the base rate.
I recommend that to successfully make predictions about the long-term results of
something such as an investment strategy or the overall direction of a market, you
must consider three things:
1. The long-term base rate of the success or failure of the strategy you are
evaluating;
2. The tendency of systems where both luck and skill are involved to revert to the
mean and;
3. What happened historically after certain extreme observations.
So, for example, when I wrote the commentary entitled “A Generational Buying
Opportunity” in March of 2009, I was not relying on any particular insight that I
might have had at the time, but rather on the data available to me about what
happens in markets after they reach an extreme inflection point. It’s important to
remember that the stock market is a complex, adaptive system with feedback loops
that has elements of both luck and skill. Luck, in the stock market, essentially holds
sway over the short-term and is a specific chance occurrence that affects the overall
market or individual stock or portfolio can be either good or bad. Luck is a residual—
it’s what is left over after you subtract skill from the outcome.
How much luck is involved determines the range of outcomes—where little luck is
involved, a good process will almost always lead to a good outcome. Where a
measure of luck is involved, a good process will usually have a good outcome, but
only over longer periods of time. The luck/skill continuum in investing is almost
entirely a function of time. Over shorter periods, your results are highly contingent
on luck and chance. This is vital to understand because you might see a bad process
provide excellent results due entirely to chance and a good process provide poor
results for the same reason.
Consider a simple intuitive strategy of buying the 50 stocks with the best annual sales
gains. But consider this not in the abstract but in the context of what had happened
in the previous five years:
Year Annual Return S&P 500 return

Year one 7.90% 16.48%
Year two 32.20% 12.45%
Year three -5.95% -10.06%
Year four 107.37% 23.98%
Year five 20.37% 11.06%
Five-year
Average Annual
Return 27.34% 10.16%
$10,000 invested in the strategy grew to $33,482 dwarfing the same investment in
the S&P 500, which grew to $16,220. The three-year return (which is the metric that
almost all investors look at when deciding if they want to invest or not) was
even more compelling, with the strategy returning an average annual return of
32.90% compared to just 7.39% for the S&P 5000. Also consider that these returns
would not appear in a vacuum—if it was a fund it would probably have a five start
Morningstar rating; it would probably be featured in business news stories quite
favorably and the “long-term” proof would say that this intuitive strategy made a
great deal of sense and would attract a lot of investors.
Here’s the catch—the returns shown are from “What Works on Wall Street” and are
for the period from 1964 through 1968, when, much like the late 1990s, speculative
stocks soared. Investors without access to the very long-term results to this
investment strategy would not have the perspective that the longer term brings, and
without these tools, might have jumped into this strategy right before it went on to
crash and burn. As the data from What Works on Wall Street makes plain, over the
very long term, this is a horrible strategy that returns less then U.S. T-bills over the
long-term. Had this investor had access to long-term returns, he or she would have
seen that buying stocks based just on their annual growth of sales was a horrible way
to invest—the strategy returned just 3.88 percent per year between 1964 and 2009!
$10,000 invested in the 50 stocks from All Stocks with the best annual sales growth
grew to just $57,631 at the end of 2009, whereas the same $10,000 invested in U.S.
T-Bills compounded at 5.57 percent per year, turning $10,0000 into $120,778. In
contrast, if the investor had simply put the money in an index like the S&P 500, the
$10,000 would have earned 9.46 percent per year, with the $10,000 growing to
$639,144! An investment in All Stocks would have done significantly better, earning
11.22 percent per year and turning the $10,000 into $1.33 million! What the investor
would have missed during the phase of exciting performance for this strategy is that,
in the end, valuation matters, a lot.
This is a good example of why Kahneman’s paper is so important—people make
forecasts not on the data, but how well the prediction fits their perspective and the
story behind it. Extrapolating from a small data set can be disastrous to long-term
results. The “Most Dangerous Equation” was derived by Abraham de Moivre and
states that the variation of the mean is inversely proportional to the size of the
sample. A small sample tells you nothing about the true direction of results. Using a
small sample—as we see above—can lead to costly errors over the long term.

What this tells us
1. Investors are well advised to look at short-term performance as a worthless
indicator for what will happen over the long-term. Indeed, short-term performance
can be among the most misleading to investors and should be heavily discounted.
The stock market combines both luck and skill, with luck more pronounced over
short time periods, and skill more telling over long periods of time.
2. Investors should make decisions using the long-term base rates a strategy
exhibits—in other words, they should concentrate on what is probable rather than
what is possible. If you organized your life around things that might possibly happen
to you, you’d probably never leave your house, and when you did, it would only be to
buy a lottery ticket. Consider, on a drive to the supermarket, it is highly probable that
you will get there, buy your groceries and get back home to unpack them without
incident. But what’s possible? Almost anything—it’s possible a plane flying overhead
could lose an engine falling directly on your car and instantly killing you.
It’s possible another car runs a red light and kills you on impact. It’s possible that you
get carjacked and your assailant kills you in the process. You get the point—anything
is possible but highly improbable. It’s only when you think in terms of probability
that you will get in your car and go, yet few investors do so when making investment
decisions. Our brains create cause and effect narratives after something has occurred
that seem to make sense, however improbable the event. Witness anyone who
invested in the stocks with the highest sales gains after a great short-term run.
3. In the stock market, short term trends are mostly random and heavily
influenced by luck. To succeed, you must ignore them and invest in strategies that
have the highest probability (base rate) of succeeding in the future.
4. You will not win the lottery. Avoid buying tickets and avoid what my son,
Patrick O’Shaughnessy, calls lottery stocks.
5. Over short periods of time, a good investment strategy can lead to poor results
just as a poor investment strategy can lead to good results. Do your homework;
understand how a strategy performs over long periods of time and stick with it. If you
can do just this one thing, you will be ahead of the vast majority of investors over the
long-term.

Thursday, 24 January 2019 Page 1
For important disclosures please refer to page 13.
Christopher Wood christopher.wood@clsa.com +852 2600 8516
Trade and the benefit of the doubt
Hong Kong
The benefit of the doubt is still given to the continuation of the risk on trade which commenced on
Boxing Day, with the S&P500 and the MSCI AC World Index up 12.4% and 9.8% respectively since
then (see Figure 1). The reason for this remains GREED & fear’s continuing base case, namely that a
US-China trade deal will be agreed within the 90-day deadline which means by 1 March. GREED &
fear’s view remains firmly that Donald Trump and Xi Jinping want such a deal.
Figure 1
S&P500 and MSCI AC World Index: Performance since the beginning of 2018
12
(%chg)
9
6
3
0
-3
-6
-9
-12
-15
S&P500
MSCI AC World Index
-18
Jan 18
Feb 18
Mar 18
Apr 18
May 18
Jun 18
Jul 18
Aug 18
Sep 18
Oct 18
Nov 18
Dec 18
Jan 19
Source: CLSA, Datastream
The past week saw some support for this view with The Wall Street Journal’s report that US Treasury
Secretary Steven Mnuchin favours removing the existing tariffs introduced last year in order to put
pressure on China to make concessions in areas such as intellectual property and market access (see
The Wall Street Journal article: “Officials Debate Cutting Tariffs”, 18 January 2019). This confirms what
GREED & fear has also been telling investors during the past two weeks of meetings in the UK and
Europe, as well as this week in terms of continuing meetings in Hong Kong. That is that it makes
sense to assume that the existing tariffs will be removed, as well as the threatened tariffs not
implemented, if a deal is done. This is important because most investors have been assuming, based
on GREED & fear’s personal observation, that the existing tariffs are staying whatever the outcome
of the current negotiations. This is why, if they are removed, it raises the potential for investors to
hope that globalisation may not be ending after all.
Still if this is the positive, it is a negative that someone has leaked this to the Journal since the
purpose of the leak was probably to try to disrupt the continuing negotiations. In this respect, it has
become very clear that Beijing is correct to try and do a deal with Trump now since other future
American presidents might prove much less friendly to Beijing amidst growing evidence of anti-
Beijing sentiment on both sides of the political aisle in Washington. Democratic Congressmen have
already begun to declare in public that Trump should not make too many concessions to China.
While last Wednesday Republican and Democratic lawmakers introduced bills that would ban the
sale of US chips or other components to Huawei, ZTE or other Chinese telecom companies that “are
in violation of the export control or sanctions laws of the United States”.

Christopher Wood christopher.wood@clsa.com +852 2600 8516
This is a reminder that the national security issues remain hard to resolve, which is also why it is
GREED & fear’s base case that they will be kept outside the current trade talks precisely because the
Donald wants to “make a deal”. That means the current export controls will remain. The US
Department of Commerce added 44 Chinese entities to its export control list in August for posing a
“significant risk” to US national security or foreign policy interests. The export controls restrict
companies’ access to products that America deems could have dual military or civilian use.
Rather the focus of the current negotiations is likely to be on China agreeing to buy American goods
by a fixed amount to reduce the bilateral trade deficit with the US, as also leaked last Friday (see
Bloomberg article: “China offers a path to eliminate US trade imbalance, sources say”, 18 January 2019),
as well as a general commitment by Beijing going forward not to offer market access as a quid pro
quo for access to intellectual property. Bloomberg reported that China has offered to increase
imports from America by a combined value of more than US$1tn over the next six years, seeking to
reduce its trade surplus with the US to zero by 2024. The offer implies increasing the annual imports
from America from US$155bn in 2018 to around US$200bn in 2019 and about US$600bn by 2024.
Figure 2
China trade of goods with the US
500
450
400
350
300
250
200
150
100
50
0
(US$bn)
China exports to US
China imports from US
China trade surplus with US
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Source: China General Administration of Customs, CEIC Data
This is the kind of “win” the Donald can sell to his supporters. Still any kind of formal US monitoring
of Chinese compliance with the deal, as has also been rumoured, will likely prove a deal breaker with
Beijing for cultural reasons. Hopefully, the Donald understands this.
Moving on from the current Sino-US discussions on trade, with Chinese Vice Premier Liu He due to
visit Washington on 30-31 January, the past week also saw support for another of GREED & fear’s
base cases. That is that the Donald still wants to do a deal on North Korea. GREED & fear refers, of
course, to the announcement that a second summit between Trump and North Korean leader Kim
Jong-un will be held late next month most likely in Hanoi. This announcement followed a 90-minute
meeting last Friday in the White House between Trump and North Korean lead negotiator Kim
Yong-chol, a former intelligence chief. It also follows Kim Jong-un’s four-day visit to Beijing earlier
this month.
One reason GREED & fear believes Trump is focused on North Korea is because he wants to register
a “win” in an area of policy where all of his predecessors have failed. Another reason is because he
has taken the view, after meeting Kim personally at the Singapore summit last June, that the North
Thursday, 24 January 2019 Page 2

Christopher Wood christopher.wood@clsa.com +852 2600 8516
Korean leader is serious about seeking to modernise his economy, a view also supported by North
Korean defectors GREED & fear has met in Seoul.
If this is the case, the street smart Trump will also understand that Kim is not going to agree to a
deal based on the demands set by Washington’s national security hawks such as national security
adviser John Bolton. This is that America will not sign any peace treaty with Pyongyang ending the
Korean War unless North Korea owns up to and shuts down all its existing nuclear facilities.
This is why Trump needs the support of Xi to try to come up with some formula which bridges the
current impasse. After all, China has long wanted Pyongyang to modernise its economy while Trump
is not pushing a reunification agenda. This is why GREED & fear was interested to read an article in
Hong Kong’s South China Morning Post on Sunday (“Nigerian mission ‘offers model to disarm N Korea’”,
20 January 2019). This reported that nuclear experts from America and China had cooperated last
year to remove highly enriched uranium from a reactor in Nigeria to prevent the material falling into
the hands of “terrorists”. In this case the material was reportedly moved to China. The article
speculated that a similar process could take place as regards the Korean issue in the sense that
North Korean nuclear weapons or material could be moved to China. Clearly, however, such an
approach would run contrary to Pyongyang’s core ideology of Juche which can be broadly
interpreted as self-reliance. Still the question is what pressure Beijing can exert on Pyongyang. On
this point, Kim has now visited China four times in the past ten months.
Figure 3
Korean export growth in US dollar terms
50
40
30
20
10
0
-10
-20
-30
-40
(%YoY)
Korean export growth
Jan 07
May 07
Sep 07
Jan 08
May 08
Sep 08
Jan 09
May 09
Sep 09
Jan 10
May 10
Sep 10
Jan 11
May 11
Sep 11
Jan 12
May 12
Sep 12
Jan 13
May 13
Sep 13
Jan 14
May 14
Sep 14
Jan 15
May 15
Sep 15
Jan 16
May 16
Sep 16
Jan 17
May 17
Sep 17
Jan 18
May 18
Sep 18
Jan 19
Note: Data up to the first 20 days of January 2019. Source: CLSA, CEIC Data
The anticipation that something is going to happen sooner or later as regards North Korea, assuming
Trump remains president, is one reason why GREED & fear has had a bigger weighting last year in
Korea than would otherwise have been the case given the combination of the current downturn in
the DRAM cycle and the self-defeating left-wing policies of the Minjoo Government, which have
resulted in an unnecessary weakening in the domestic economy at a time when the external sector is
slowing. Korean exports declined by 14.6% YoY in the first 20 days of January, after falling by 1.3%
YoY in December (see Figure 3). In terms of the damage done to the domestic economy, GREED &
fear refers to the decline in job growth triggered by aggressive minimum wage hikes and the
collateral damage likely to result from renewed aggressive property tightening. This was discussed
at some length recently (see GREED & fear - The deleveraging dialectic, 13 December 2018). On job
Thursday, 24 January 2019 Page 3

Christopher Wood christopher.wood@clsa.com +852 2600 8516
growth, total employment increased by only 34,000 jobs year-on-year in December (see Figure 4),
down from 316,000 in 2017.
Figure 4
Korea YoY increase in total employment
1,000 (YoY, thousands)
YoY change in Korea employment
800
600
400
200
0
-200
Dec 09
Apr 10
Aug 10
Dec 10
Apr 11
Aug 11
Dec 11
Apr 12
Aug 12
Dec 12
Apr 13
Aug 13
Dec 13
Apr 14
Aug 14
Dec 14
Apr 15
Aug 15
Dec 15
Apr 16
Aug 16
Dec 16
Apr 17
Aug 17
Dec 17
Apr 18
Aug 18
Dec 18
Source: CLSA, CEIC Data, KOSIS
Any kind of deal on North Korea will mean the Korean market finally becomes interesting from a
macroeconomic perspective for the first time in many years. This is because it will create the
potential for a long-term investment cycle in North Korea, a country of 25m, where the model is
likely to be Shenzhen-style special economic zones not German wage unification. In the meantime,
the Korean market remains for now a play on DRAM with Samsung and Hynix accounting for
roughly 45% of reported profits in the first three quarter of last year.
GREED & fear has no claim to be an expert on DRAMs or tech. Still there is one fundamental point
about the latest semiconductor cycle which makes it conceptually different from any of its
predecessors. That is that it was driven to a significant extent by a capital spending cycle, and not
just by the demand for a tech toy, be it a smartphone or a laptop. That is the building of data centres.
On this point, CLSA’s Seoul-based analyst Sanjeev Rana has published a report this week which
forecasts a re-acceleration in data centre capex in the second half of 2019 (Korea technology – Data
centre Capex acceleration in 2H, 21 January 2019). The current sudden collapse in growth is viewed
as a reset following a 50% surge in 2018 in what Rana calls “hyper-scale cloud capex”. The estimate
is that last year Amazon Web Services (AWS), Google, Microsoft, Apple and Facebook accounted for
over 70% of that activity. The prediction is for a 4% YoY decline in the first quarter of this year
followed by a more than 20% YoY increase in the second half of 2019 as inventory is digested by
end-1H19 and new server CPU launches in 2Q19 drive renewed demand.
The above is of interest to GREED & fear. But whether the pickup in spending is that soon may also
depend on what is happening to the share prices of those drivers of demand which include four of
the five FAANG stocks. On that issue, GREED & fear’s base case is that the current rally in US
equities is only a countertrend move, and that it is risky for investors to assume that the downturn
in US equities has ended until Fed balance sheet contraction ends. This is because GREED & fear’s
base case is that balance sheet contraction is more influential on assets prices, while rate hikes
impact the level of economic activity as evidenced by the continuing slowdown in US housing in
recent quarters. US existing home sales declined by 6.4% MoM and 10.3% YoY to an annualised
4.99m units in December, the lowest level since November 2015 (see Figure 6).
Thursday, 24 January 2019 Page 4

Christopher Wood christopher.wood@clsa.com +852 2600 8516
Figure 5
FANG stocks index
210
190
170
150
(End 2016=100)
FANG stocks index
50-day mov. avg.
200-day mov. avg.
130
110
90
70
Jan 16
Mar 16
May 16
Jul 16
Sep 16
Nov 16
Jan 17
Mar 17
May 17
Jul 17
Sep 17
Nov 17
Jan 18
Mar 18
May 18
Jul 18
Sep 18
Nov 18
Jan 19
Note: Market cap weighted at the end of 2016. Include Facebook, Amazon, Netflix and Google (Alphabet). Source: CLSA, Bloomberg
Figure 6
US new home sales and existing home sales
7,500 (thousand, saar)
(thousand, saar)
7,000
US existing home sales
6,500
US new home sales (RHS)
6,000
5,500
5,000
4,500
4,000
3,500
3,000
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Source: US Census Bureau, National Association of Realtors
2019
1,400
1,300
1,200
1,100
1,000
900
800
700
600
500
400
300
200
Meanwhile it has become clear that the current shutdown of the US federal government, now into
its fifth week and the longest in history, has started to become an issue for markets. This is because
it has gone on for long enough that it has begun to impact the economy with an estimated 800,000
workers not being paid and government contractors put on hold.
The base case must be that a deal will be done sooner rather than later with Donald Trump making
his first attempt at a compromise on Saturday by offering to extend protection for some
undocumented immigrants in return for US$5.7bn in funding for his Mexican “wall”, a move quickly
rejected by the Democratic side. That the Donald is now seeking terms suggests that he now
realises he has messed up on this issue since he went ahead with the shutdown probably without
realising some of the technical consequences. The result is that he is now being blamed for the
problem, with his support rating declining to 40.9% (see Figure 7), while the Democrat leadership in
Congress has all the leverage. Still the Democrats should not squeeze too hard since they risk
overplaying their hand if the Donald continues to show an uncharacteristic desire to compromise.
Thursday, 24 January 2019 Page 5

Christopher Wood christopher.wood@clsa.com +852 2600 8516
Figure 7
President Donald Trump’s approval rating
48
46
(%)
President Donald Trump's approval rating
44
42
40
38
36
Jan 17
Feb 17
Mar 17
Apr 17
May 17
Jun 17
Jul 17
Aug 17
Sep 17
Oct 17
Nov 17
Dec 17
Jan 18
Feb 18
Mar 18
Apr 18
May 18
Jun 18
Jul 18
Aug 18
Sep 18
Oct 18
Nov 18
Dec 18
Jan 19
Source: Bloomberg, RealClearPolitics Poll Average
Hopefully from a trade standpoint, the 45 th American president is not weakened too much politically
by this current impasse since that might make it harder for him to strike the preferred deal with
China. Still GREED & fear would hope that the government shutdown has ended well before the 1
March deadline for the trade deal.
Figure 8
China nominal and real GDP growth
29
24
19
14
9
4
(%YoY)
Nominal GDP growth
Real GDP growth (RHS)
(%YoY)
Mar 00
Sep 00
Mar 01
Sep 01
Mar 02
Sep 02
Mar 03
Sep 03
Mar 04
Sep 04
Mar 05
Sep 05
Mar 06
Sep 06
Mar 07
Sep 07
Mar 08
Sep 08
Mar 09
Sep 09
Mar 10
Sep 10
Mar 11
Sep 11
Mar 12
Sep 12
Mar 13
Sep 13
Mar 14
Sep 14
Mar 15
Sep 15
Mar 16
Sep 16
Mar 17
Sep 17
Mar 18
Sep 18
16
15
14
13
12
11
10
9
8
7
6
Source: CLSA, CEIC Data, National Bureau of Statistics
Returning to the China story, in a week when newspaper headlines were proclaiming that China
growth has fallen to a 28-year low, it is worth noting that the just released Chinese economic data is
nothing like as bad as the hype. There are a couple of points worth making about this set of data.
First, while the real GDP growth is now the slowest in 28 years, nominal GDP is much healthier. Real
GDP growth slowed to 6.4% YoY in 4Q18 and 6.6% YoY for the whole year, the slowest annual
growth since 1990, while nominal GDP growth slowed from 9.4% YoY in 3Q18 to 9.1% YoY in 4Q18
and was 9.7% YoY in 2018 (see Figure 8). This is well above the levels of nominal GDP growth
recorded in 2015 when it slowed to 6.4% YoY in 4Q15 and 7% in 2015.
Second, the broadest and most accurate measure of Chinese consumption, featured in GREED &
fear’s current presentation material, remains remarkably healthy amidst the current bearish
sentiment. Thus, consumption expenditure per capita growth rose from 7.1% YoY in nominal terms
Thursday, 24 January 2019 Page 6

Christopher Wood christopher.wood@clsa.com +852 2600 8516
and 5.4% YoY in real terms in 2017 to 8.4% and 6.2% in 2018, though slowing from 8.8% and 6.7%
YoY in 1H18 (see Figure 9). It is worth making the point again that this data series includes both
consumption of goods and services. Unfortunately most investors, as well as the press, still focus on
retail sales when looking at Chinese consumption. But this only measures the purchase of goods in
China. Yet the richer China becomes the more that will be spent by consumers on services.
Figure 9
China consumption expenditure per capita growth
12
(%YoY YTD) Real growth Nominal growth
11
10
9
8
7
6
5
Mar 14
Jun 14
Sep 14
Dec 14
Mar 15
Jun 15
Sep 15
Dec 15
Mar 16
Jun 16
Sep 16
Dec 16
Mar 17
Jun 17
Sep 17
Dec 17
Mar 18
Jun 18
Sep 18
Dec 18
Source: CEIC Data, National Bureau of Statistics
Still if the above points are important, it should be noted that concerns will inevitably grow about
China’s economy if GREED & fear’s base case is wrong and there is no trade deal. This is because the
result will be a further deterioration in employment. On this point, conditions in the job market
began to worsen last quarter as a result of the first wave of US tariff increases implemented in July-
September.
Figure 10
CRR SME Unemployment Index
100 (DI)
90
80
70
60
50
40
30
20
10
0
2Q07
4Q07
2Q08
4Q08
2Q09
4Q09
Unskilled factory workers
2Q10
4Q10
2Q11
4Q11
2Q12
4Q12
2Q13
4Q13
2Q14
Note: An index reading above 50 implies that more SMEs are finding it easier to hire, thus indicating an overall increase in unemployment.
Source: China Reality Research (CRR)
4Q14
Skilled/managerial workers
2Q15
4Q15
2Q16
4Q16
2Q17
4Q17
2Q18
4Q18
Such is the message from the just published China Reality Research (CRR) SME quarterly survey of
300 private SME manufacturers (see CRR report SME Quarterly: Survival mode, 24 January 2019).
CRR’s SME Unemployment Index picked up in 4Q18 with more firms finding it easier to hire,
implying the supply of idle labour has increased. The unemployment index for unskilled factor
workers, a diffusion index based on the changes in difficulties SME employers face in hiring
compared to the previous year, rose from 38 in 3Q18 to 41 in 4Q18, the first increase since 1Q17,
while the index for skilled workers also rose from 34 to 36 (see Figure 10). Less than 20% of the
Thursday, 24 January 2019 Page 7

Christopher Wood christopher.wood@clsa.com +852 2600 8516
SMEs added staff in 4Q18, the lowest level since 4Q15, while some 30% said they plan to cut staff
in the coming quarter, the highest level since the series began in 1Q09 (see Figure 11).
Figure 11
CRR SME survey: % of SMEs plan to increase/decrease staff size in the next quarter
(% of respondents)
Increase Keep the same Decrease
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1Q09
2Q09
3Q09
4Q09
1Q10
2Q10
3Q10
4Q10
1Q11
2Q11
3Q11
2Q12
3Q12
4Q12
1Q13
2Q13
3Q13
4Q13
1Q14
2Q14
3Q14
4Q14
1Q15
2Q15
3Q15
4Q15
1Q16
2Q16
3Q16
4Q16
1Q17
2Q17
3Q17
4Q17
1Q18
2Q18
3Q18
4Q18
Source: China Reality Research (CRR)
This is why, in a world where no deal on trade is agreed and the threatened tariff increases are
implemented, the odds of a more significant stimulus rise significantly. But this is clearly not the
preferred option of Beijing policymakers. Finally, returning to the recent macro data, it is also worth
noting that manufacturing investment rose by 11.6% YoY last quarter and 9.5% YoY in 2018 (see
Figure 12). This data point has been in a rising trend since bottoming in mid-2016 and certainly
contrasts with the current legitimate concerns about a loss of private sector confidence.
Figure 12
China manufacturing fixed asset investment growth (%YoY YTD)
40
35
30
25
20
15
10
5
0
(%YoY YTD)
Manufacturing sector FAI
Jan 07
Jun 07
Nov 07
Apr 08
Sep 08
Feb 09
Jul 09
Dec 09
May 10
Oct 10
Mar 11
Aug 11
Jan 12
Jun 12
Nov 12
Apr 13
Sep 13
Feb 14
Jul 14
Dec 14
May 15
Oct 15
Mar 16
Aug 16
Jan 17
Jun 17
Nov 17
Apr 18
Sep 18
Source: CEIC Data, National Bureau of Statistics
Environmental, social and governance (ESG) is clearly all the rage in the fund management industry,
most particularly in Europe. While major buy-side firms continuing to proclaim in public their
commitment to the “sustainable” cause, GREED & fear knows from meetings with individual fund
managers that the real views on this phenomenon often differ markedly from what is aired in the
official marketing material. Already this year GREED & fear has heard ESG described as a “fraud” by
one investor, who interestingly has a fervent belief in man-made global warming, and as “a scam to
justify higher fees” by another. GREED & fear will naturally not disclose the sources.
Thursday, 24 January 2019 Page 8

Christopher Wood christopher.wood@clsa.com +852 2600 8516
If this is the reality under the bonnet, GREED & fear’s own issue with ESG is how it is possible to
define “sustainable”. There clearly is huge room for subjective judgments on this subject, which
makes ESG a bonanza for tick-in-the-box consultants. This point was brought home to GREED & fear
by news reports last year that one Scandinavian institution had decided not to include Facebook in
its ESG portfolios, a decision GREED & fear would be personally sympathetic to but doubtless many
other buy-side firms would not.
Meanwhile the point of raising ESG this week is to recommend a recent Hello Investors report by
CLSA’s portfolio strategist Matthew Sigel, which focuses on how the major passive fund managers
have begun to use “their bully pulpit in a bid to influence the environmental, social and governance
(ESG) priorities of their portfolio companies” (see CLSA research Hello Investors - ESG distorts
capitalism, 16 January 2019). Sigel argues that asset owners and fund managers who accept (and
even pay for) benchmarks that purport to standardise ESG criteria are sacrificing what used to be
called “alpha” to an oligopoly cleverly trying to deflect the emerging negative backlash against their
increased voting power as shareholders given the massive increase in indexation in the past ten
years. Assets of US index mutual funds and index ETFs totalled US$6.7tn at the end of 2017,
accounting for 35% of total assets in US long-term funds, up from US$1.4tn or 15% of total fund
assets at the end of 2007, according to the Investment Company Institute (see Figure 13).
Figure 13
US index mutual funds and ETFs % of US long-term funds’ total assets
7
6
5
4
3
2
1
(US$tn) US index mutual funds & ETFs
(%)
as % of US total long-term funds (RHS)
35
30
25
20
15
10
0
5
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Source: Investment Company Institute
GREED & fear could not agree more with the above points. As for indexation, it remains nothing but
investor socialism. The latest passive boom should have peaked with the commencement of Fed
balance sheet contraction. Unfortunately, however, GREED & fear cannot rule out renewed Fed
balance sheet expansion at some point in the not too distant future. Indeed GREED & fear would
count on it. But assets in passive funds will have declined in the interim, hopefully discrediting in the
process the passive concept. GREED & fear says hopefully since that is an outcome GREED & fear
would not count on given the obvious appeal of buying indexes in a rising market.
Finally, some changes will be made to the long-only portfolios. The investment in Sunny Optical in
the Asia ex-Japan long-only portfolio will be removed and replaced by an investment in the Samsung
Electronics Preferred share, which has a forecast 2019 dividend yield of 5% (see Figure 14). Despite
the sharp correction last year, Sunny Optical’s share price is still up 581% since inclusion in the
portfolio in September 2014. Meanwhile, the dividend yield on the Samsung Preferred is now higher
than that of TSMC.
Thursday, 24 January 2019 Page 9

Friday, 11 January 2019 Page 1
For important disclosures please refer to page 15.
Christopher Wood christopher.wood@clsa.com +852 2600 8516
Shaken and stirred
London
Fund managers entered 2019 shaken and stirred judging by GREED & fear’s meetings in London this
week. So more of a relief rally would not surprise, most particularly given the absence of the
traditional year-end rally, though the S&P500 bottomed on Boxing Day and is now up 10%. Still
GREED & fear remains of the view that the bear market action has not ended even though GREED &
fear also remains hopeful that Asia’s relative underperformance has maxed out.
The triggers for the relief rally that commenced this week clearly relate to the twin topics of trade
and tightening which also form the headline of the latest Asia Maxima (Trade and tightening, 1Q19).
On trade GREED & fear’s base case remains that a deal will be done between America and China
within the allocated 90-day period for reasons often discussed here; though it is clearly a positive
that trade negotiators commenced talks on Monday in Beijing. On tightening there has been a more
substantive development when Fed Chairman Jerome Powell went out of his way last Friday to
reassure markets that he was ready to respond quickly to data if needed and that, effectively,
quantitative tightening was not on autopilot. Powell said at an annual meeting of the American
Economic Association in Atlanta last Friday that the Fed “will be prepared to adjust policy quickly
and flexibly”. He also noted, “If we came to the view that the balance sheet normalisation or any
other aspect of normalisation was part of the problem, we wouldn’t hesitate to make a change”. It is
also interesting that Powell was reading from prepared notes during the speech, presumably to
make sure he was “on message”.
For the market those comments were treated as more relevant than the latest US job and wage data
which, ostensibly, make it harder for the Fed to stop tightening. US nonfarm payrolls rose by
312,000 jobs in December, up from 176,000 in November and the biggest increase in 10 months.
While average hourly earnings growth accelerated from 3.1%YoY in November to 3.2%YoY in
December, matching the level in October which was the highest level since April 2009 (see Figure 1).
Figure 1
US increase in non-farm payrolls and average hourly earnings growth
('000)
Increase in US nonfarm payrolls (LHS)
600
Average hourly earnings growth for private employees
400
200
0
-200
-400
-600
-800
-1,000
Jan 07
May 07
Sep 07
Jan 08
May 08
Sep 08
Jan 09
May 09
Sep 09
Jan 10
May 10
Sep 10
Jan 11
May 11
Sep 11
Jan 12
May 12
Sep 12
Jan 13
May 13
Sep 13
Jan 14
May 14
Sep 14
Jan 15
May 15
Sep 15
Jan 16
May 16
Sep 16
Jan 17
May 17
Sep 17
Jan 18
May 18
Sep 18
(%YoY)
4.0
3.5
3.0
2.5
2.0
1.5
Source: US Bureau of Labour Statistics

Christopher Wood christopher.wood@clsa.com +852 2600 8516
To GREED & fear the market is correct to pay more attention to Powell’s comments than the job and
wage data, which is why stocks rallied and the US dollar corrected last Friday (see Figure 2). This is
because rising wage pressure is a classic “late cycle” indicator while all the money and credit data
indicate a slowdown is coming in America this year, be it M2 growth, loan growth or bank deposit
growth (see GREED & fear – Asset prices and the Fed, 3 January 2019). Meanwhile a further indication
of the weakness in the housing sector came with the latest US pending homes sales (of existing
homes) which declined by 7.7%YoY in November, the 11 th consecutive month of year-over-year
decline (see Figure 3).
Figure 2
S&P500 and US Dollar Index
3,000
S&P500
US Dollar Index (RHS)
98.0
2,900
97.5
2,800
97.0
96.5
2,700
96.0
2,600
95.5
2,500
2,400
95.0
94.5
94.0
2,300
Jul 18 Aug 18 Sep 18 Oct 18 Nov 18 Dec 18 Jan 19
Source: Bloomberg
93.5
Figure 3
US pending home sales index %, YoY
30
(%YoY)
US pending home sales index
20
10
0
-10
-20
-30
2002 2004 2006 2008 2010 2012 2014 2016 2018
Source: National Association of Realtors, Datastream
Still if Powell’s change of language has started to reduce investor concerns it has to be remembered
that quanto tightening for now proceeds at a rate of US$50bn a month, the consequence of which
will be increasingly negative. Yet it will probably take more negative market action to prompt the
Fed to stop even if it may have effectively paused as regards the prospects of more Fed rate hikes.
The other point, of course, is that the release of the Fed minutes on Wednesday has made it evident
that many Fed governors were having second thoughts about more tightening at the time of the
December FOMC meeting.
Friday, 11 January 2019 Page 2

Christopher Wood christopher.wood@clsa.com +852 2600 8516
It is also interesting that Powell in his comments last Friday cited 2016 as an example of when the
Fed was prepared to go on hold in response to market action. While this was indeed the case it
should be remembered that there is a big difference between then and now. The 2016 “risk-off”
action was very much centred on the collapse in the oil price and the resulting related spike in US
junk bond yields dominated as they were then by the shale sector (see Figure 4). By contrast, the
current “risk-off” action is coming after 15 months of tightening in terms of balance sheet
contraction and after three years of rates hikes, which began in December 2015.
Figure 4
US high-yield corporate bond spread
9
(ppt)
US High-Yield corporate bond spread
8
7
6
5
4
3
Jan 11
Jul 11
Jan 12
Jul 12
Jan 13
Jul 13
Jan 14
Jul 14
Jan 15
Jul 15
Jan 16
Jul 16
Jan 17
Jul 17
Jan 18
Note: Based on the Bloomberg Barclays US High-Yield Corporate Bond Index. Source: Bloomberg
Jul 18
Jan 19
Meanwhile, if there is growing evidence in coming months that the American economy is really
slowing, the market will be increasingly hoping for not just an end of tightening but also renewed
easing. But it is going to take the Fed time to go from “double whammy” monetary tightening (i.e.
rate hikes and quanto tightening) to renewed easing unless there is a complete market breakdown
triggered by surging credit spreads. Meanwhile for those looking for a change in Fed policy sooner
rather than later, the risk is that GREED & fear’s base case of a trade deal between US and China
delays this by creating the catalyst for more of a countertrend equity rally led by Asia.
Some support for such a continuing rally will also have been provided by the latest easing measures
from China, including a RRR cut. The PBOC announced last Friday a 100bp cut in the reserve
requirement ratio (RRR) to 13.5% for large banks (see Figure 5). The move will be implemented in
two phases, with a 50bp cut on 15 January and another 50bp on 25 January. The central bank also
stated that the medium-term lending facility (MLF) maturing in 1Q19 will not be rolled over. These
moves will release a net Rmb800bn in liquidity into the financial system. Beijing will also soon unveil
larger-scale tax cuts and tax exemptions for small and micro enterprises (SMEs), according to a
statement released after a State Council executive meeting chaired by Premier Li Keqiang on
Wednesday. The tax incentives will cover all taxes incurred since 1 January, and will be effective for
a tentative three years. They are expected to save about Rmb200bn per year for the SMEs. But
GREED & fear hears that more tax cuts are pending, focusing on cuts in the VAT rates.
Still the reaction of the A share market to the latest PBOC move has been nothing like as exuberant
as Wall Street’s to Powell’s comments last Friday (see Figure 6). Meanwhile GREED & fear has found
a noticeable deterioration in investor sentiment towards China in London this week with the view
being propounded by some of the more extreme bears that China is already “pushing on a string” in
Friday, 11 January 2019 Page 3

Christopher Wood christopher.wood@clsa.com +852 2600 8516
the sense that that term became fashionable as regards the extended deflationary malaise in post-
Bubble Japan.
Figure 5
China reserve requirement ratios
24
22
(%) RRR for large banks RRR for small banks
20
18
16
14
12
10
8
6
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Source: Bloomberg, PBOC
Figure 6
China CSI 300 Index
4,400
4,200
China CSI 300 Index
4,000
3,800
3,600
3,400
3,200
3,000
2,800
Jan 16
Mar 16
May 16
Jul 16
Sep 16
Nov 16
Jan 17
Mar 17
May 17
Jul 17
Sep 17
Nov 17
Jan 18
Mar 18
May 18
Jul 18
Sep 18
Nov 18
Jan 19
Source: Bloomberg
In GREED & fear’s view such an interpretation is way too extreme. China is only just beginning to exit
from a self-induced deleveraging agenda, which is why it will be very important to monitor China’s
credit data for any sign of an upturn in coming months. Meanwhile the growing assortment of
targeted easing measures being announced should help ensure that the slowdown in growth
bottoms out in the first half of this year. CLSA’s head of economic research, Eric Fishwick, expects
China’s growth to bottom in 1Q19 (see CLSA research Eye on Asian Economies – Groundhog year, 12
December 2018).
Still the key risk to this assumption is the residential property market, where the trend is slowing in
contrast to the infrastructure investment which has clearly bottomed. GREED & fear also remains of
the view that the deleveraging pressure in the mainland stock market peaked last year. The best
reason to believe this, as previously discussed here, is that the bond refinancing schedule of A share
companies peaked last year. To highlight this point again GREED & fear reproduces a chart below by
CLSA’s head of China Capital Access, Alexious Lee, (see Figure 7 and China Thru Trains – Signalling
buybacks, 29 October 2018) shown in a previous report.
Friday, 11 January 2019 Page 4

Christopher Wood christopher.wood@clsa.com +852 2600 8516
Figure 7
China A shares – total value of pledged shares and corporate bonds due
3,500
(Rmbbn)
Pledged shares due
Bond repayment
3,000
2,500
2,000
1,500
1,000
500
0
1Q17 2Q17 3Q17 4Q17 1Q18 2Q18 3Q18 4Q18 1Q19 2Q19
Source: Wind, CITIC Securities, CLSA
The other point about China, which relative-return fund managers in the emerging market space will
not need reminding of, is that MSCI is due to decide by the end of February on how much to
increase A shares’ representation. This is likely to keep Northbound flows strong. Stock Connect
Northbound net inflows totalled Rmb294bn in 2018, up from Rmb200bn in 2017. Northbound
inflow is forecast to rise to Rmb300-400bn in 2019 on further MSCI/FTSE inclusion (see Figure 8
and CLSA research China Thru Trains: Connecting China – 1Q19, 4 January 2019). Southbound flows
are a different matter. Stock Connect Southbound net outflows have been HK$43bn since April
2018 (see Figure 9). Meanwhile, H shares are now trading at a weighted average 15% discount to
their A share counterparts, down from 27% in February 2018 (see Figure 10).
Figure 8
Hong Kong Stock Connect Northbound flows
60
50
(Rmb bn)
Stock Connect Northbound flow (Shenzhen-HK and Shanghai-HK)
40
30
20
10
0
(10)
(20)
(30)
(40)
Nov 14
Jan 15
Mar 15
May 15
Jul 15
Sep 15
Nov 15
Jan 16
Mar 16
May 16
Jul 16
Sep 16
Nov 16
Jan 17
Mar 17
May 17
Jul 17
Sep 17
Nov 17
Jan 18
Mar 18
May 18
Jul 18
Sep 18
Nov 18
Jan 19
Note: Data up to 10 January 2019. Source: HKEx, Bloomberg, CLSA
Friday, 11 January 2019 Page 5

Christopher Wood christopher.wood@clsa.com +852 2600 8516
Figure 9
Hong Kong Stock Connect Southbound flows
100 (HK$bn)
Stock Connect Southbound flow (Shenzhen-HK & Shanghai-HK)
80
60
40
20
0
(20)
(40)
Nov 14
Jan 15
Mar 15
May 15
Jul 15
Sep 15
Nov 15
Jan 16
Mar 16
May 16
Jul 16
Sep 16
Nov 16
Jan 17
Mar 17
May 17
Jul 17
Sep 17
Nov 17
Jan 18
Mar 18
May 18
Jul 18
Sep 18
Nov 18
Jan 19
Note: Data up to 10 January 2019. Source: HKEx, Bloomberg, CLSA
Figure 10
China H shares premium/discount to A shares
20
10
0
-10
-20
-30
-40
-50
(%)
China H shares premium/discount to A shares
-60
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Note: Based on the Hang Seng China A/H Premium Index. Source: Datastream, Hang Seng Indexes, CLSA
With all the focus on the US-China trade negotiations, it is easy to forget about Taiwan. But there
was an interesting New Year speech on Taiwan made by Chinese President Xi Jinping on 2 January
which is worth highlighting. Xi called on Beijing and Taipei to start talks on unification and the
adoption of “one country, two systems” in Taiwan, laying out steps to settle the 70-year-old division
between the two sides. He said: “The problem of Taiwan existed because the Chinese nation was
weak and in chaos, but it will end along with national rejuvenation.”
Xi also said Taiwanese independence should not be tolerated and representatives from both sides
should “start in-depth democratic consultations for a cross-Strait relationship and the future of the
Chinese nation, and reach transitional arrangements for the peaceful development of cross-Strait
ties” (see South China Morning Post article: “Chinese President Xi Jinping urges Taiwan to follow Hong
Kong model for unification”, 2 January 2019).
Xi’s more assertive tone may in part represent Beijing’s desire to take advantage of the main political
development in Taiwan last quarter. That was the unexpectedly heavy losses suffered by the ruling
Democratic Progressive Party (DPP) in the local city elections held in late November. The party
Friday, 11 January 2019 Page 6

Christopher Wood christopher.wood@clsa.com +852 2600 8516
ended up in charge of just six of Taiwan’s 22 cities and counties. By contrast, the opposition
Kuomintang won 15 cities and counties, including the traditional DPP stronghold of Kaohsiung.
The defeat was sufficiently crushing for President Tsai Ing-wen to step down as leader of the DPP,
which has prompted speculation that she may not be the DPP presidential candidate for the next
presidential election due to be held in January 2020. Meanwhile Beijing has undoubtedly seen the
outcome as an endorsement of its strategy of not talking to the DPP government ever since Tsai
refused to acknowledge the formula of One China, Two Systems in her inauguration speech in May
2016.
Even allowing for the natural tendency to vote anti-incumbent in mid-term elections, the results
have renewed the focus on the lack of progress in cross-Strait relations and the resulting negative
economic consequences for the domestic Taiwan economy, including an ongoing brain drain. An
estimated 2m Taiwanese businessmen and their families live in China. Meanwhile, China accounts
for more than 40% of Taiwan’s exports, of which 80% are intermediate goods assembled in China
before being sold domestically or exported. Worryingly, a survey seen by GREED & fear and
conducted in May 2018 found that 88% of Taiwanese office and factory employees are interested in
working overseas, including in the mainland. Such data will only encourage Beijing in its continuing
efforts to entice more Taiwanese to move. For example, the Taiwan Affairs Office of the State
Council announced in February 2018 a package of 31 measures designed to give greater access to
Taiwanese companies and individuals on the mainland.
Still, the reliance of Taiwanese companies on China as a production centre has become a perceived
risk in the context of the current US-Sino trade dispute. This has raised hopes in Taiwan for
manufacturing reshoring. The National Development Council announced at the end of November a
scheme to facilitate the return of companies. The plan, which includes the provision of industrial
land, began on 1 January and run for an initial period of three years. However, there is massive
scepticism about the prospects of this initiative. One obvious problem is sourcing skilled labour.
Figure 11
Taiwan export growth in US dollar terms
30 (%YoY, 3mma)
20
Total exports
Exports of electronic products
Exports to China
10
0
-10
-20
Jan 11
May 11
Sep 11
Jan 12
May 12
Sep 12
Jan 13
May 13
Sep 13
Jan 14
May 14
Sep 14
Jan 15
May 15
Sep 15
Jan 16
May 16
Sep 16
Jan 17
May 17
Sep 17
Jan 18
May 18
Sep 18
Source: CEIC Data
Another issue is the lack of available power supply, as well as the related need for new investments
to satisfy environmental-impact concerns. The DPP had been committed to close down all of
Taiwan’s four nuclear power plants, which currently account for 10% of electricity supply, by 2025.
Yet GREED & fear understands that there are no concrete plans in place on how to replace them
Friday, 11 January 2019 Page 7

Christopher Wood christopher.wood@clsa.com +852 2600 8516
beyond vague talk about “renewables”. Still, the Executive Yuan approved a draft revision to the
Electricity Act in early December to abandon that 2025 deadline as a result of one of the
referendums voted on in the local elections, where a majority (59.5% of valid votes) voted in favour
of repealing the related paragraph of the electricity law which stated that all nuclear-based power
plants “shall wholly stop running by 2025”. In what looks like a classic fudge, Premier Lai Ching-te
has stated that the revision “does not change the goal of transforming Taiwan into a nuclear-free
homeland, but rather eliminates a specific deadline for achieving that objective”.
Meanwhile from a macro perspective, the export sector has slowed as the downturn in the
technology sector has become more visible, with total exports declining by 3% YoY in US-dollar
terms in December and total electronics exports contracting by 9.9% YoY (see Figure 11). This
slowing trend has already been signalled by foreigners selling a net NT$355bn worth of Taiwan
stocks last year (see Figure 12) while the Taiex Electronics Index is down 20% from its peak reached
in late January 2018 (see Figure 13). As ever in Taiwan, there is scant ability for the domestic
economy to offset the external weakness. Still, the Tsai government will now come under pressure
to do more to stimulate domestic demand, given the poor election results. The fiscal deficit is
estimated by CLSA’s economics team to remain at 1.9% of GDP this year. Real GDP growth is
forecast to slow to 2.4% this year, down from an estimated 2.6% in 2018.
Figure 12
Cumulative foreign net buying of Taiex stocks
1600 (NT$bn)
1400
Cumulative foreign net buying of Taiex stocks
1200
1000
800
600
400
200
0
-200
-400
-600
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Source: CEIC Data, Taiwan Stock Exchange, CLSA
Figure 13
Taiex Electronics Index
500
450
Taiex Electronics Index
400
350
300
250
200
150
100
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Source: Datastream
Friday, 11 January 2019 Page 8

Christopher Wood christopher.wood@clsa.com +852 2600 8516
From a stock market valuation perspective, CLSA’s Taiwan tech universe of 49 stocks under
coverage trades at 13.4x 2019 earnings based on forecast earnings growth this year of 2.8%. This is
slightly below the historical 10-year average forward PE of 13.8x (see Figure 14). The same universe
has a forecast dividend yield this year of 4.5%.
Returning to the cross-Strait theme, Xi also upped the ante in his New Year speech by stating that
the political division across the Strait “cannot be passed on from generation to generation”. This is a
warning that the status quo is not long term acceptable, a significant development given Xi’s term in
power no longer has term limits. This suggests he is intent on resolving the Taiwan issue during his
period in power. Meanwhile, Tsai’s defiant response to Xi’s speech, made just hours after the speech,
was that “Taiwan will never accept one country, two systems, and that the majority opinion in
Taiwan is also against it”.
All this is a reminder to investors that the cross-Strait issue cannot be ignored altogether.
Figure 14
CLSA Taiwan tech sector universe 12-month forward PE
19
(x)
18
17
16
+1s.d.
15
14
mean
13
12
11
-1s.d.
10
Jan 09
Jun 09
Nov 09
Apr 10
Sep 10
Feb 11
Jul 11
Dec 11
May 12
Oct 12
Mar 13
Aug 13
Jan 14
Jun 14
Nov 14
Apr 15
Sep 15
Feb 16
Jul 16
Dec 16
May 17
Oct 17
Mar 18
Aug 18
Jan 19
Source: CLSA evalu@tor
Figure 15
Philippines CPI inflation and BSP key policy rate
12 (%) BSP key overnight RRP rate
Core CPI inflation (%YoY)
10
CPI inflation (%YoY)
8
6
4
2
0
-2
Jan 02
Jul 02
Jan 03
Jul 03
Jan 04
Jul 04
Jan 05
Jul 05
Jan 06
Jul 06
Jan 07
Jul 07
Jan 08
Jul 08
Jan 09
Jul 09
Jan 10
Jul 10
Jan 11
Jul 11
Jan 12
Jul 12
Jan 13
Jul 13
Jan 14
Jul 14
Jan 15
Jul 15
Jan 16
Jul 16
Jan 17
Jul 17
Jan 18
Jul 18
Note: Overnight reverse repurchase (RRP) rate. Source: CEIC Data, Bangko Sentral ng Pilipinas (BSP)
Elsewhere in Asia, Philippines inflation fell by more than expected in December to 5.1%YoY, down
from 6.0% in November (see Figure 15). This was well below the 6.7% peak in September but still
above the BSP’s 2-4% inflation target. Despite the fall in inflation, CLSA’s Asean economist Anthony
Friday, 11 January 2019 Page 9

Christopher Wood christopher.wood@clsa.com +852 2600 8516
Nafte argues that the central bank should remain mindful of robust domestic demand (see CLSA
research Infofax Daily – Philippines Inflation: Rate rise not ruled out, 7 January 2019).
This makes sense to GREED & fear. Unlike India and Indonesia, this is a late cycle economy with a
twin deficit. Nafte’s estimates are 2.3% of GDP for the current account deficit and 3% of GDP for
the fiscal deficit in 2018. While the forecasts for 2019 are 2.7% and 3.2% of GDP respectively. The
current account deficit was 2.7% of GDP in the first three quarters of 2018, up from 0.7% in 2017
(see Figure 16). While the fiscal breakdown for the first eleven months of 2018 shows expenditure
growth at 24.1%YoY outpacing revenue growth at 16.4%YoY (see Figure 17). This is in the context
of an overall government debt to GDP ratio of 42%.
Figure 16
Philippines current account balance as % of GDP
6
5
4
3
2
1
0
(1)
(2)
(3)
(4)
(%GDP)
Philippines current account as % of GDP
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
9M18
Source: BSP, CLSA
Figure 17
Philippines government revenue and expenditure growth
25
(%YoY)
Government expenditure
Government revenue
20
15
10
5
0
(5)
(10)
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
11M18
Source: CEIC Data, CLSA
Corporate earnings have so far remained relatively healthy, in the face of 175bp of monetary
tightening since last May, rising by 9%YoY in the first three quarters of 2018. This reflects the
continuing private-sector-driven investment cycle which is now into its eighth year. Real investment
growth accelerated to 15.3%YoY in the first three quarters of 2018 (see Figure 18) in the context of
forecast real GDP growth of 6.4% last year. While credit growth is running at 16.8%YoY in
November, though down from 18.1% in October (see Figure 19). CLSA’s economics team forecasts
Friday, 11 January 2019 Page 10

Christopher Wood christopher.wood@clsa.com +852 2600 8516
an acceleration in real GDP growth to 6.8% in 2019 on continuing investment-led growth, combined
with a recovery in consumption. Meanwhile a growing feature of the investment cycle last year was
rising government spending on infrastructure. This is expected to continue. Government
infrastructure spending rose by 42% YoY in the first 11 months of 2018 (see Figure 20).
The strong investment-driven growth means the rising current-account deficit as a percentage of
GDP has now become the major macro risk. The risk of further current account deterioration is now
officially recognised by Bangko Sentral with the central bank having recently raised its forecast for
the current account deficit to 1.9% of GDP in 2018 and 2.3% in 2019.
Figure 18
Philippines real GDP and gross fixed capital formation growth
30
(%YoY) Real GDP growth Real GFCF growth
25
20
15
10
5
0
(5)
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 9M18
Source: CEIC Data, CLSA
Figure 19
Philippines bank loan growth and nominal GDP growth
60
(%YoY)
Philippines bank loan growth
Nominal GDP growth
50
40
30
20
10
0
-10
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Note: Net of banks’ reverse repurchase transactions with the BSP. Source: CEIC Data, BSP, CLSA
Friday, 11 January 2019 Page 11

The Investor Seth Klarman, in a Rare Interview, Offers a Warning
Davos is having a down year. Every winter, attendance at the World
Economic Forum, in the Swiss Alps, provides an informal checkup on the
health of global capitalism. China has posted its slowest growth in twentyeight
years, and President Xi Jinping is staying home; France is beset by
protests, and President Emmanuel Macron has sent his regrets; and
America is slogging through the longest government shutdown in its
history, forcing President Donald Trump to cancel his trip. So it’s fitting
that one of the most talked-about people at Davos this year is also not in
attendance: Seth Klarman, a low-key but highly influential investor based in
Boston, whose recent annual letter to investors represents what Andrew
Ross Sorkin, of the Times, calls “a huge red flag about global social
tensions, rising debt levels and receding American leadership.”
Klarman, who is sixty-one, is the C.E.O. and portfolio manager of the
Baupost Group, a hedge fund with twenty-seven billion dollars in assets.
Owing to his success in making long-term bets on stocks that he considers
undervalued, he is frequently compared to Warren Buffett. (Klarman is
nicknamed the Oracle of Boston.) His 1991 book, “Margin of Safety,”
which argues for resisting the fads of Wall Street, is long out of print, but
regularly sells on Amazon for more than a thousand dollars. His latest
letter, a twenty-two-page report that is circulating in Davos, states that “it
can’t be business as usual amid constant protests, riots, shutdowns and
escalating social tensions.”
Klarman is concerned about more than political disarray. He doesn’t give
many interviews, but, when I contacted him recently, he agreed to speak
because, he said, shortsighted business practices are imperilling public
confidence in capitalism itself. Among business leaders, he told me, “I think
people realize that we’re not where we should be.” He added, “It’s maybe
not an inappropriate ask to say, ‘Let’s all look at just where we were taking
things for granted, and where maybe we were shortchanging.’ We took the
game we were playing for granted—whether that’s investing, or business,
or politics.”
In 2016, Harvard’s Institute of Politics found that only forty-two per cent of
millennials supported capitalism. Klarman believes that he and his peers
need to prevent their field from being defined by some of its worst actors.
“People will say the words ‘Wall Street’ with a derogatory tone. They’re

talking about an immoral place, where there’s just disgusting amounts of
greed and nothing good happens—which isn’t fair and isn’t true.” He said,
“I’m not on Wall Street, I’m in Boston, but you’re tarred with that brush.”
On balance, he said, “We’re complicated individuals. Each of us is good in
this way; we’re not good in that way.”
In various forms, Americans are engaged in a growing debate over the
fundamentals, and the future, of the market economy. Senator Elizabeth
Warren is building a Presidential campaign partly around the Accountable
Capitalism Act, a bill she introduced last year that, among other proposals,
would give workers the right to elect forty per cent of seats on corporate
boards. Oxfam, in its latest report on inequality, calculates that the
combined fortunes of the world’s twenty-six richest people reached a
record $1.4 trillion last year, equal to the total wealth of the 3.8 billion
poorest people. In “Can American Capitalism Survive?,” a new book that is
attracting attention in Washington, Steven Pearlstein, a Pulitzer Prizewinning
business columnist at the Washington Post, contends that the
singular focus on “maximizing shareholder value” has “led business leaders
to abandon their role as proud stewards of the American system.”
For a generation of business leaders, maximizing shareholder value has
been a central doctrine, a theory that is invoked to justify cutting jobs and
benefits in order to reward investors with dividends and stock buybacks.
But, in a speech at Harvard Business School last fall, Klarman argued that
American capitalism has been damaged by the obsession with short-term
stock prices. “Does anyone really believe that shareholders are the only
constituency that matters: not customers, not employees, not the
community or the country or Planet Earth?” he asked.
In those remarks, Klarman challenged C.E.O.s and fellow-investors to
accept greater responsibility for the consequences of their actions. “It’s a
choice to do things that ‘maximize profits,’ to pay people as little as you
can, or work them as hard as you can,” he said. “It’s a choice to maintain
pleasant working conditions or, alternatively, particularly harsh ones, to
offer good benefits or paltry ones.” Also, without naming specific cases, he
criticized the kind of buyouts in which private-equity investors saddled a
troubled company with so much debt that it helped push the company into
bankruptcy. (The collapse of Toys R Us is a recent example.) He said, “It’s a
choice to leverage up your company to the hilt, to pile on non-recourse
debt to pay special dividends to the owners, and then walk away if the
business falters and the debt comes due. Just because you can do
something definitely doesn’t mean that you should.”

In conversation, Klarman is both candid and prone to self-reflection. At one
time, he was New England’s largest donor to the Republican Party. He has
attracted criticism from liberals for backing conservative causes, and
from activists who wanted his fund to cancel its holdings of Puerto Rican
debt after Hurricane Maria. But, since the 2016 election, Klarman has been
outspoken in his conviction that Donald Trump poses a grave threat to
democracy. The shock of Trump’s victory was, to Klarman, an urgent
warning. “When I’m confronted with some world event that I don’t
understand, like when 9/11 happened,” he said, he thinks, “Oh, my god,
the world has been evolving while I wasn’t paying enough attention, and
I’d better pay attention.” In the 2018 midterms, he donated heavily to
Democratic candidates and to organizations dedicated to shoring up the
rule of law, like Protect Democracy. He said, “Evolving is usually called ‘flipflopping,’
but, as humans, who are we if we don’t evolve? I’m proud that I
evolve, because I think people who fail to evolve and learn are part of the
problem.”
Raised in Baltimore—his father was an economist and his mother a social
worker—Klarman picked his first stock when he was ten years old. He
graduated from Cornell, and, after business school at Harvard, he joined
Baupost at its launch, in 1982. In the decades since, he has watched
investors and corporate executives become increasingly fixated on
boosting stock prices at any cost. “I’m convinced, as an investor, that the
world I live in every day has gotten more short-term-oriented,” he said.
“The pressure on the game changed the game.” Some investors, he said,
are too quick to demand ephemeral fixes: “Why aren’t you restructuring?
Why aren’t you doing a spinoff? Why aren’t you buying back stock?’ ”
In his view, companies that operate with integrity rarely get enough credit
for it from investors or the press. “You have people who are princes, who
have good values, who treat people right. We don’t tend to pay a lot of
attention; we don’t get a lot of stories about them. The surveys of the most
admired businesses—how much do those evolve over time based on your
market cap? What’s in vogue and in favor is ‘admired.’ ” He has watched,
with chagrin, as Wall Street firms pocketed billions in fees and
commissions by steering clients to bad deals that they dismiss as
“O.P.M.”—Other People’s Money. “Talking about clients as though they are
to be taken advantage of rather than to be honored, and respected, and
cherished, as your lifeblood—it’s disgusting, but you see that in individual
behavior.” He added, “When one person does that, it’s bad for all the rest
of us.”
He told me, “I don’t think it’s too late for business leaders to start doing
the right thing for their employees, their clients, and their communities.”

And if they don’t? It could lead to regulations that, in his mind, would go
too far in constraining corporate behavior. In his speech, he said, “When
capitalism goes unchecked and unexamined, and management is seduced
by a narrow and myopic perspective, the pendulum can quickly swing in
directions where capitalism’s benefits are discounted, and its flaws
exaggerated.” Klarman hopes that politicians in Washington will hear his
message, but, more to the point, he wants fellow-practitioners to hear him.
“If every businessperson, or enough businesspeople, don’t act as stewards
of more than just the bottom line, somebody’s going to come along and
do it for them.”
Klarman’s critiques of Washington and of irresponsible business practices
share a common target: the selfish disregard for the future. “If we think of
free enterprise and democracy as games, a lot of people are breaking the
rules and disrespecting the other players and even the game itself. Mitch
McConnell is disrespecting the game. Donald Trump doesn’t even know
what the rules are. Free enterprise has been good for me and for the
world. It has been good for my two-hundred and eighty employees. It has
been good for my clients. Let’s honor the system. Let’s make sure that we
leave and improve it for the next generation to benefit just as much as we
did and with as much respect as we showed.” Otherwise, he said, “What
kind of scorched-earth cost might we have to pay for that?”

Indicator Release
ECONOMY RELEASE CALENDAR
February 2019
India Equity Research | Economy
Given below is a calendar indicating significant economic events/releases due in
February 2019:
For India, Union Budget, PMI, inflation, industrial production, trade deficit will be
of significance.
Globally, data released on manufacturing indices, money supply and
unemployment will continue to be keenly watched.
Table 1: Major releases for India
Date Economy Data release / Event Period Exp Prior
1-Feb India Union Budget Feb
1-Feb India Nikkei India PMI Manufacturing Jan 53.2
5-Feb India Nikkei India PMI Services Jan 53.2
7-Feb India RBI repo rate (%) Feb 6.5
9-Feb India Domestic PV sales (YoY) Jan (0.4)
12-Feb India Industrial Production (% YoY) Dec 0.5
12-Feb India CPI YoY Jan 2.2
15-Feb India Trade Deficit (USD bn) Jan (13.1)
15-Feb India Exports (% YoY) Jan 0.3
28-Feb India GDP (% YoY) Q3FY19 7.1
Table 2: Major releases for US
Date Economy Data release / Event Period Exp Prior
1-Feb US ISM Manufacturing Jan 54 54.3
1-Feb US Change in non farm payrolls ('000) Jan 165 312
1-Feb US Unemployment Rate Jan 3.9 3.9
4-Feb US Durable Goods Orders Nov 1.7 0.8
5-Feb US Retail Sales Ex Auto (% MoM) Dec 0.1 0.2
15-Feb US Industrial Production (% MoM) Jan 0.3
19-Feb US NAHB Housing Market Index Feb 58.0
21-Feb US Existing Home Sales (mn) Jan 5.0
Table 3: Major releases for other major economies
Date Economy Data release / Event Period Exp Prior
1-Feb Eurozone PMI Manufacturing Jan 51 50.5
5-Feb Eurozone Retail sales (%, YoY) Dec 1.1
10-Feb China Money Supply M2 (%, YoY) Jan 8.1
11-Feb China Foreign Reserves (USD Trillion) Dec 3.1
13-Feb Eurozone Industrial Production SA (MoM) Dec (1.7)
14-Feb China Exports (% YoY) Jan (4.4)
15-Feb China CPI (%, YoY) Jan 1.9
Source: Bloomberg
Prateek Parekh, CFA
+91-22-6623 3469
prateek.parekh@edelweissfin.com
January 31, 2019
Edelweiss Research is also available on www.edelresearch.com,
1 Edelweiss Securities Limited
Bloomberg EDEL , Thomson First Call, Reuters and Factset.