Update from the risk parity managers - City of San Jose Retirement ...

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REDISTRIBUTION. THESE MATERIALS DO NOT CONSTITUTE AN OFFER TO SELL OR A 

SOLICITATION OF AN OFFER TO BUY SECURITIES. 

Credit Suisse Asset Management 

Commodities 

Presentation for: City of San Jose 1961 Police & Fire 

Department Retirement Plan and the City of San Jose 

1975 Federated City Employees Retirement System 

December 12, 2012 

Christopher Burton 

Senior Portfolio Manager 


New York 

Telephone +1 (212) 325 7319 

e-mail: christopher.burton@credit-suisse.com 

Credit Suisse Asset Management, LLC 

The following presentation was produced to the best of our knowledge and in good conscience according to the Global Investment Performance Standards (GIPS®). However, only an 

official GIPS® report or a company can comply with the GIPS®. An official GIPS® report in line with GIPS®, a list of all composites and a verification report have either been enclosed or 

are available on request. 

Please see “Important Legal Information” for important disclosures regarding the data and information contained and the views and opinions expressed in this material.

Table of Contents 

1. Commodities at Credit Suisse 

2. Risk Parity Strategy 

3. Appendix 

4. Important Legal Information 


Slide 2

1. Commodities at Credit Suisse 


Slide 3

Credit Suisse Asset Management: Focused Investment Solutions 

We are a client-centric organization dedicated 

to providing focused investment solutions to 

investors worldwide. 

We leverage Credit Suisse’s best ideas, 

access, resources and capabilities globally to 

establish long-term partnerships with clients to 

help them thrive. 

We offer a deep talent pool with over 740 

investment professionals, 49 traders, 96 

quantitative analysts, 32 economists/research, 

38 strategists and 24 market risk specialists. 

We deliver the full strength of our 

global franchise through: 

� Seasoned investment expertise 

� Broad capabilities and partnerships 

� Intellectual capital 

� Comprehensive risk management 

� Dedicated client service 

As of September 30, 2012 

2 Assumes USD/CHF conversion rate of 1.064 as of September 30, 2012. 

Asset Management at a Glance 1 

Date of Establishment 1935 

Assets Under Management $392.5 billion 2 

Number of Employees 2,800 

Global Reach and Local Presence 

Credit Suisse Offices* 

Asset Management Credit Suisse 

Located in 19 countries Located in 52 countries 


Slide 4

A Leading Portfolio Management Team 

Credit Suisse has been proactive in recruiting talent from across the industry as well as from within our world class 

organization and top academ ic institutions globally 

Name Position Background and Experience 

Nelson Louie Global Head of 

CSAM 

Commodities 

Christopher Burton Head of Portfolio 

Management 

Tim othy Boss Fixed Income 

Portfolio Manager 

Christopher Kem pton Client Portfolio 

Manager 

Nelson Louie acted as Portfolio Manager for the Total Commodity Return Strategy from 1994 – 2007 where he oversaw the 

Team and was responsible for developing the research process for the enhanced commodity strategy. Nelson rejoined Credit 

Suisse in August 2010 as Global Head of CSAM Commodities, focusing on the portfolio management and strategic 

development of the business. 

Christopher Burton, CFA, FRM, joined the Team as a Portfolio Manager in 2005, managing the Credit Suisse Commodities 

Strategy with Nelson Louie. In addition to his portfolio management role, Mr. Burton contributed significantly to leading and 

expanding the CSAM commodities platform from 2007-2010. 

Tim Boss joined in June 2009 as the fixed income portfolio manager. Tim previously served as a fixed income trader within the 

Fixed Income group at Credit Suisse. 

Chris Kempton, CFA, joined the Team in 2011 as the Client Portfolio Manager/ Product Specialist. He is responsible for client 

and product development activities for the Team. Mr. Kempton received his MBA from London Business School. 

Frank Lu Vice President Frank Lu, CFA, joined the Team in 2011 and is responsible for researching and developing the team's quantitative alpha 

models, risk models and infrastructure. He earned his Ph.D. in Computer Engineering from Rutgers University. 

Philip Mulholland Associate Philip Mulholland, CFA, joined Credit Suisse in 2009 after completing his M.B.A. at the London Business School. Philip 

focuses on commodity research and trading. 

Fanny Chen Associate 

Fanny Chen joined the strategy in July 2009 as part of the Credit Suisse Analyst Participant Program after receiving a B.A. in 

Economics and M.A. in Statistics at Harvard. Fanny interned with the group in 2008 and currently focuses primarily on the 

Commodities portion of the strategy. 

Lorenzo De Roni Analyst Lorenzo De Roni joined the team as an Analyst in the summer of 2012 upon graduating from Northwestern University with a 

B.A. in Economics and Mathematics. Lorenzo spent the summer of 2011 as an intern in the group. He focuses on the 

Commodities portion of the strategy. 

Eliza Baker Marketing Associate Eliza Baker joined the strategy in 2011 as a Marketing Associate focusing on marketing and client services. She was hired 

into Credit Suisse's Investment Bank in 2007 where she worked in Commodities Sales for four years. Eliza received her B.S. 

from the University of Georgia. 

Christina Chan Marketing Analyst Christina Chan joined the strategy in 2011 as a Marketing Analyst focusing on marketing and client services. She received her 

B.S. from Cornell University. 


Slide 5

Credit Suisse Asset Management Commodities Organization 

Private Banking & Wealth Management 

Asset Management 

Global Head of Commodities 

Nelson Louie 

Managing Director, Portfolio Manager 

Christopher Burton 

Managing Director 

Portfolio Manager 

Tim Boss 

Vice President 

Frank Lu 


Philip Mulholland 

Associate 

Fanny Chen 

Associate 

Lorenzo De Roni 

Analyst 

Christopher Kem pton 


Client Portfolio Manager 

Eliza Baker 

Marketing Associate 

Christina Chan 

Marketing Analyst 

Shared Services 

AM General 

Counsel 

Roger 

Machlis 

AM 

Compliance 

Em idio 

Morizio 

Global Head 

of AM Risk 

Tony Patti 


Slide 6

CSAM Range of Commodity Strategies 

β 

α 

Structure 

Availability 

Dow Jones–UBS 

Com modity Index 

Standard Benchm arks 

Low 

Enhanced Index 

(Since 1994) 

CS Com m odity 

S&P GSCI 

Benchm arks 

Risk Parity 

Active Strategy - ACCESS 

(Since 2010) 

Targeted Excess Return / Tracking Error 

Mutual Funds Private Funds Subadvised Funds 

� CS Com m odity Return Strategy 

Fund 

� Credit Suisse Trust - Com m odity 

Return Strategy Portfolio 

� Credit Suisse Com m odity 

ACCESS Strategy Fund 

� Credit Suisse Fund (Lux) 

Com m odity Index Plus (CHF, 

USD) 

� Credit Suisse Enhanced 

Com m odity Fund 

� CS Risk Parity Com m odity Fund, 

L.P. 

� CS Access Com m odity Fund, Ltd. 

� CS Nova (Lux) Com m odity Plus 

USD 

� CS Nova (Lux) Com m odity Plus 

Treasury Collateral 

� CS Nova (Lux) CS GAINS 

Com m odity Plus 

Custom 

Minimum Investment: $25m 

GAINS 

(Since 2009) 

Other Custom 

Benchm ark 

Custom Benchm arks 

High 

Separate Account 

Custom 

Minim um Investm ent: $50m 


Slide 7

Potential Risks of Investing in Commodities 

� Market-driven risk could negatively affect the value of a particular 

investment 

� Credit risk may occur if a counterparty defaults or is unable to honor a 

financial obligation 

� Commodity-linked derivatives may be subject to greater volatility than 

traditional securities. These derivatives may be affected by: 

� changes in overall market movements, 

� commodity index volatility, 

� changes in interest rates; and 

� factors affecting a particular industry or commodity, such as drought, 

floods, weather, livestock disease, embargoes, tariffs and international 

economic, political and regulatory developments 

� Speculative Nature of Commodities Investments. Investing in commodities 

is speculative and involves a high degree of risk. There is no assurance 

that technical and risk management techniques, as well as the investment 

decisions made by the investment manager, will not expose investors to 

risk of significant losses. 


Slide 8

2. Risk Parity Strategy 


Slide 9

Current Construction Methodologies of Well Known Commodity Indices 

Physical 

Characteristics 

Economic 

Significance 

Diversified Indices 

Open Interest 

Investability 

Average Monthly Historical Futures Volatilities (1/ 96 – 11/ 12, Annualized) 

Liquidity 

Transparency 

Source: Bloomberg; Credit Suisse. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse has not sought 

to independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 

Com m odities measured by: Dow Jones-UBS Commodity Index TR, composed of futures contracts on 20 physical commodities. The index is unmanaged, assumes reinvestment of dividends and does 

not reflect the deduction of fund fees and expenses. Investors cannot invest directly in an index. Volatility measured by closing prices of contracts. 


Slide 10

Characteristics of the DJ-UBS Commodity Index 

30% 

25% 

20% 

15% 

10% 

5% 

0% 

Natural Gas 

Crude Oil 

Unleaded Gasoline 

Crude Oil accounts is only 16% of the index but has 

historically accounted for 24% of the risk in the index 

Heating Oil 

Wheat 

Corn 

Soybeans 

Sugar 

Cotton 

Livestock accounts for over 6% of the index but, historically, 

has accounted for less than 1% of the risk in the index 

Coffee 

$ Weight in % Risk Weight in % 

Source: Bloomberg and Credit Suisse as of December 31, 2011. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse has not 

sought to independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 

Commodities measured by: Dow Jones-UBS Commodity Index, composed of futures contracts on 20 physical commodities. The index is unmanaged, assumes reinvestment of dividends and does not reflect the deduction of 

fund fees and expenses. Investors cannot invest directly in an index. Volatility measured by closing prices of contracts. 

Soybean Oil 

Live Cattle 

Lean Hogs (PG) 

Aluminum 

Copper 

Zinc (LZ) 

Nickel 

Gold (GL) 


Slide 11 

Silver

CSAM Risk Parity Strategy Highlights 

� Volatility is estimated 

each month 

� Cross-commodity 

correlations within 

sectors are assumed 

to be 0 

� New sector return 

series are calculated 

each month along 

with estimated 

volatility* 

� Cross-correlations of 

new sector returns 

are assumed to be 0 

Physical 

Characteristics 

Risk Parity 

Energy 

Sector 

Econom ic 

Significance 

Risk Parity 

Agriculture 

Sector 

Volatility 

Target Risk Parity Across Com m odities within Each Sector 

Risk Parity 

Livestock 

Sector 

Target Risk Parity Across Sectors within Strategy 

CSAM 

Risk Parity 

Strategy 

Open Interest 

Investable 

Risk Parity 

Industrial Metals 

Sector 

Liquidity 

Transparency 

Risk Parity 

Precious Metals 

Sector 

Key Differences 

By assuming no correlation when deriving the weights of the commodities within the sectors and then the sectors themselves, it 

potentially increases diversification characteristics. Typically, there is a positive correlation between commodities as well as 

sectors. This would imply that any mean-variance optimization process would over-weight those commodities or sectors with 

lower volatility and lower cross-commodity correlation. 

*Note – alternative methodology is applied when a new commodity is added for which data is unavailable 


Slide 12

Commodity Exposures – Comparison of Risk Parity Strategy vs. 

Popular Indices 

As of November 30, 2012 

Energy 

Agriculture 

Livestock 

Industrial 

Metals 

Precious 

Metals 

Sector 

Risk Parity 

Benchmark Weights 

DJ-UBS Index 

TR Weights 

S&P GSCI TR 

Weights 

Natural Gas 2.74% 11.82% 2.48% 

Crude Oil 3.04% 8.08% 28.91% 

Gasoline 3.06% 3.21% 5.25% 

Heating Oil 3.48% 3.30% 5.25% 

Brent Oil 3.32% 4.93% 18.40% 

Gasoil 3.40% - 4.83% 

Wheat 2.45% 6.55% 3.77% 

Corn 2.49% 7.45% 5.35% 

Soybeans 3.00% 8.14% 2.77% 

Sugar 2.27% 2.98% 1.60% 

Cotton 2.67% 1.47% 0.95% 

Coffee 2.93% 1.67% 0.63% 

Soybean Oil - 3.13% - 

KC Wheat 2.57% - 1.10% 

Cocoa 2.80% - 0.25% 

Live Cattle 12.03% 3.76% 2.90% 

Lean Hogs 6.62% 2.09% 1.52% 

Feeder Cattle 10.24% - 0.47% 

Aluminum 4.46% 5.66% 2.12% 

Copper 3.59% 7.17% 3.28% 

Zinc 3.53% 3.28% 0.54% 

Nickel 3.02% 2.32% 0.57% 

Lead 2.95% - 0.42% 

Gold 8.70% 9.91% 3.15% 

Silver 4.65% 3.07% 0.53% 

Dow Jones-UBS Commodity 

Index TR 

Industrial 

Metals 

19% 

Livestock 

6% 

Precious 

Metals 

13% 

CSAM Risk Parity Strategy 

Benchmark 

Industrial 

Metals 

18% 

Livestock 

29% 

Precious 

Metals 

13% 

Source: Bloomberg; Credit Suisse . All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse has not 

sought to independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 

Energy 

31% 

Agriculture 

31% 

Energy 

19% 

Agriculture 

21% 

S&P Goldman Sachs 

Commodity Index TR 

Livestock 

5% 

Agriculture 

16% 

Industrial 

Metals 

7% 

Precious 

Metals 

4% 


Slide 13 

Energy 

68%

Risk Parity Strategy Additional Information 


Annualized Returns Com parison 

1/ 31/ 91 – 

11/ 30/ 2012 

CSAM Risk 

Parity Strategy* 

DJ-UBS TR S&P GSCI TR S&P 500 

BarCap US 

Aggregate (Bond) 

Return (annualized) 5.53% 5.20% 3.73% 8.92% 6.81% 

Volatility 11.30% 15.02% 21.02% 14.93% 3.67% 

Correlation to DJ-UBS 0.90 1.00 0.90 0.31 0.04 

Correlation to GSCI 0.76 0.90 1.00 0.25 0.02 

Source: Bloomberg; Credit Suisse. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse has not sought to independently verify 

information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 

The hypothetical backtested performance for the CSAM Risk Parity Strategy ("RP Strategy") is from January 31, 1991 to March 31, 2011. The performance for the RP Strategy from March 31, 2011 to November 30, 2012 

represents live performance of the strategy. The returns are calculated by allocating weights across commodities as represented by the S&P GSCI single commodities indices. The returns listed were not available for direct 

investment and are provided solely for analysis purposes. Results do not represent actual trading and may not reflect the impact that material economic and market factors might have had on an adviser’s decision-making if an 

adviser were actually managing clients’ money. The RP Strategy is not a product that a client can directly invest into. Clients may invest in the Credit Suisse Risk Parity Commodity Fund, L.P, which is based on the RP Strategy 

and incepted on March 31, 2011. Past performance is no guarantee or indicator of future results. 


Slide 14

Enhanced Indexing: Risk Parity Commodity Fund, L.P. 

The Right Benchm ark 

INDEX SELECTION 

Spot Return + Roll Yield + Collateral Yield = Total Return 

DJ - UBS Index TR 

SPOT RETURN 

Price return based on weights 

specified in DJ - UBS Index TR 

ROLL YIELD 

Return impact due to 

migration of futures position 

from near to far contract 

COLLATERAL YIELD 

Return earned on pledged 

collateral 

Risk Control 

CS Risk Parity 

Credit Suisse Value Added: 

Relative weights are 

determined by targeting equal 

intra - sector and then inter - 

sector volatilities 

Credit Suisse Value Added: 

Identification of structural 

inefficiencies that seek to add 

value through the 

management of the roll 

Credit Suisse Approach: 

Conservative cash 

management seeks to avoid 

any unintended correlation to 

fixed income or equity markets 


Slide 15

Credit Suisse Total Commodity Return – Enhanced Indexing 

Objective 

� Seeks to outperform the benchmark through active management of the roll process, while maintaining a 

pure exposure to commodities using a conservative cash strategy 

Philosophy 

� Access an index with a transparent process and liquid underlying instruments 

� Isolate correlative benefits without taking spot risk or other unintended risks 

� Obtain beta exposure without paying high embedded fees 

� Conservative cash management 

� Offer flexible investment options, i.e. customized benchmarks, separate accounts and commingled 

vehicles 

� Advantage: Employ an active roll process to exploit market inefficiencies 


Slide 16

Roll Yield 

Rolling commodity index futures is a major component of return: 

� The index is a price index of a basket of near-term commodity futures 

� The index rolls 20% of the futures forward on the 5th-9th business day each month at the closing price 

� The gain or loss from this roll yield is a significant component in calculating total return 

� Quantitative and qualitative spread analysis based on market conditions is used to determine when to roll 

Passive method for maintaining futures market exposure: 

� CURRENT MONTH � 

S M T W T F S 

1 2 3 4 5 W 

W 6 7 8 9 10 W 

W 11 12 13 14 15 W 

W 16 17 18 19 20 W 

20% of index value is rolled forward to next month on the 5 th –9 th business day 

Roll 


Slide 17

Determining When to Roll: 

Qualitative & Quantitative Evaluation Process 

Quantitative Analysis 

Qualitative Overlay 

Risk Assessment 

Relative Value Trading 

Opportunity 

Seasonal 

Analysis 

Current Market 

Conditions 

Optimization 

Intra-day Rolling 

During 5 Day 

Cycle 

Trends and Mean 

Reversion 

News/ Event 

Driven Risk 

Liquidity & 

Transaction Cost 

Analysis 

Rolling Outside 

Standard 5 Day 

Cycle 

Inter/ Intra-Market 

Spreads 

Actions of Current 

Market 

Participants 

Volatility Analysis 

Curve Positioning 

Roll 


Slide 18

Risk Control 

� Daily: 

− Performance evaluated to monitor tracking risk 

− Foreign exchange exposure monitored, when 

applicable 

− Cash, variation margin reconciled 

� Controls in place to monitor deviations versus the 

Spot Return, Roll Yield, and Collateral Yield 

� Established processes ensure physical delivery is 

never undertaken 

SPOT RETURN 

Price return on real asset 

ROLL YIELD 

Return impact due to 

migration of futures position 

from near to far contract 

COLLATERAL YIELD 

Return earned on pledged 

collateral 

Risk Monitored on Real Time Basis 

TOTAL 

RETURN 


Slide 19

Conservative* Cash Management 

Collateral 

“Style Pure” 

Process 

� Benchmark for most indices is 90-day U.S. T-Bill 

− Purchasing and holding does not guarantee benchmark return 

� Greater duration or credit risk can increase correlation with other asset classes 

� Low risk: focus on preservation of principal and liquidity 

� Discipline risk control 

� Assess client objectives including liquidity, maturity and other requirements 

� Construct cash portfolio to reflect market strategies consistent with client objectives 

� Monitor and reinvest portfolio 

* The collateral management portion of the Commodities Strategy invests in US Treasuries and US Agency Debt. US Agency debt does not constitute an obligation 

of the United States and is not guaranteed by the United States. 

Collateral 


Slide 20

Spot Return: Pros and Cons of Futures Contracts Versus Swaps 

Swaps Futures 

Pros 

Cons 

Pros 

Cons 

Availability of intraday liquidity 

Increased opportunity to add value from roll yield 

Ability to manage market impact risk 

Exchange listing guarantees performance of contracts 

Closing settlement prices not guaranteed 

Higher explicit and implicit costs 

More moving parts 

Fixed fee structure 

Transfer risks and costs of rolling contracts to dealer 

Simplicity in using one vehicle 

Closing prices can be guaranteed 

Less opportunity to add value from roll yield 

Inability to manage market impact risk 

Counterparty risk 

Spot 


Slide 21

Risk Parity Commodity Fund, L.P. 

Objective 

� The Credit Suisse Risk Parity Commodity Fund seeks to provide exposure to a volatility adjusted strategy 

comprised of a liquid, diversified basket of commodity futures. 

Philosophy 

� Adds another dimension to risk mitigation as the target commodity exposures will be rebalanced based on 

the volatility of each constituent commodity. 

� The monthly rebalanced weights target equal intra-sector commodity volatilities, then inter-sector 

volatilities. 

� All of the benefits of the Enhanced Strategy: 

− Access an index with a transparent process and liquid underlying instruments 

− Isolate correlative benefits without taking spot risk or other unintended risks 

− Obtain beta exposure without paying high embedded fees 

− Conservative cash management 

− Access to alpha through the active roll process seeking to exploit market inefficiencies 


Slide 22

Credit Suisse Risk Parity Commodity Fund, L.P. 

Performance 


Nov ’12 3 Month YTD 1 Year 

Since 

Inception* 

Risk Parity Commodity Fund (Gross) 1.61% 0.83% 3.44% -0.07% -5.30% 

Risk Parity Commodity Fund (Net) 1.57% 0.70% 2.96% -0.57% -5.68% 

Credit Suisse Risk Parity Benchmark 1.51% 0.53% 2.74% -0.80% -5.81% 

Excess returns (Gross) vs. Risk Parity 0.10% 0.30% 0.70% 0.73% 0.51% 

Excess returns (Net) vs. Risk Parity 0.06% 0.18% 0.22% 0.23% 0.13% 

Dow Jones-UBS Commodity Index TR 0.05% -2.18% 1.59% -2.22% -9.71% 

Excess returns (Gross) vs. DJ-UBS 1.56% 3.01% 1.85% 2.15% 4.41% 

Excess returns (Net) vs. DJ-UBS 1.52% 2.88% 1.37% 1.65% 4.03% 

*Inception date: March 31, 2011. Performance greater than one year is annualized. 

Source: Credit Suisse Asset Management, LLC. 

Past performance is no guarantee or indicator of future results. 

Annualized 


Slide 23

3. Appendix 


Slide 24

A World Class Commodities Platform 

A Commitment Seeking to Deliver Top Performance and Develop Innovative Client Solutions Sets Credit Suisse Apart: 

Commodities Expertise 

Track Record 

Pure Exposure 

Efficient Exposure 

Bringing Our Talent and Ideas to Our Clients 

� World-class commodities team led by industry veterans with extensive derivatives backgrounds 

� Portfolio Management Team with over 20 years of combined experience in the space 

� Experience managing indexed commodities since 1994 

� $10.9 billion in assets under management globally (as of November 30, 2012) 

� Commodities asset class has exhibited positive long-term gains that are uncorrelated to fixed 

income or equity 

� Gain access to emerging growth in Asia 

� Cash management strategy which seeks to preserve the diversification qualities of the 

benchmark 

� Efficient access to commodities using standard or customized indices 


Slide 25

Globally Integrated Risk Management Capability 

Credit Suisse Asset Management offers a world-class global risk management platform with expertise across 

core competencies and clearly defined risk management accountability. 

Risk and Quantitative Analysis 

� Focus on: 

� Performance Analysis 

� Attribution Analysis 

� Exposure and Risk Analysis 

� Target Audience: 

� Senior Management: Monthly 

reviews 

� Portfolio Management: Daily 

interaction 

� Asset classes covered include 

single manager hedge funds, fund 

of hedge funds, equities, bonds, 

private equity, structured products, 

real estate, currencies and 

commodities 

Counterparty Risk Management 

� Mitigation of counterparty risk through 

rigorous credit and exposure 

monitoring 

� Risk-based approach in the reviewapproval 

of counterparties 

� Strict criteria for over-the-counter 

derivative selection 

Investment Guideline 

Monitoring Overview 

� Full-time team dedicated 

specifically to investment guideline 

monitoring: 

� Prepare client month-end 

certifications 

� Review and approve all new 

and amended client investment 

guidelines 

� Daily monitoring/review on 

adherence to investment 

guidelines and Bank Restricted 

Securities Lists 


Slide 26

CSAM Range of Commodity Strategies 

* Can hold commodities outside the benchmark universe. 

Target Excess Returns 

Enhanced Index 

Active Strategy 

(ACCESS) 

GAINS 

β Target Risk (Relative to Benchm ark) 

α 

Enhanced Index Active Strategy 

(ACCESS) 

GAINS GAINS ARCS 

Target Tracking Error 

(%) 

1.0-1.5% 4.0-7.0% 10.0% + 5.0-15.0% 

Index Exposure Spot/Sector Neutral Over/underweight and short* Over/underweight Long/Neutral/Short 

Track Record Since 1994 Since 2010 Since 2009 TBD 

Available Vehicles 

GAINS ARCS 

UCI (SICAV) Europe ✔ X ✔ TBD 

UCITS (Europe) ✔ X ✔ TBD 

Limited Partnership/Ltd. X ✔ ✔ TBD 

Collective Trust (US) ✔ X X TBD 

Registered (US) ✔ ✔ X TBD 

Separate Accounts 

(All Regions) 

✔ 

✔ 

X 

TBD 


Slide 27

2012 Commodity Index Returns as of November 30, 2012 

YTD Index Weight Notable Individual YTD 

Individual DJ UBS Sector Total Returns Returns (30 Nov '12) Performance Returns 

Dow Jones - UBS Commodity TR Index +1.59% 

Precious Metals +10.49% 12.98% Silver +17.94% 

Agriculture +8.84% 31.40% Soybean +26.40% 

Industrial Metals +1.42% 18.43% Zinc +7.83% 

Livestock -3.97% 5.85% Live Cattle -5.29% 

Energy -7.56% 31.34% Natural Gas -25.73% 

Past perform ance is no guarantee or indicator of future results. 

Source: Bloomberg. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse has not sought to 

independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 


Slide 28

Commodity Exposures – Index Choices: DJ-UBS and 

S&P GSCI Indices 

Dow Jones-UBS Commodity Index TR (DJ-UBS) 

Data since 1991 

� Weighted by production and liquidity, rebalance annually 

� Broadly diversified – 20 commodities 

− 5 energy products 

− 6 metals 

− 9 agricultural products 

� Commodities set into 7 groups, limited to 33%, at beginning of 

year 

� No single commodity may constitute less than 2% or more than 

15% in the index at the beginning of the year 

DJ-UBS as of 11/ 30/ 2012 

Industrial Metals 

19% 


13% 

Livestock 

6% 

Energy 

31% 

Agriculture 

31% 

S&P Goldman Sachs Commodities Index TR (S&P GSCI) 

Data since 1970 

� Weighted by average world production of last 5 years 

� Broadly diversified – 24 commodities 

− 6 energy products 

− 7 metals 

− 11 agricultural products 

S&P GSCI as of 11/ 30/ 2012 

Agriculture 

16% 



Industrial Metals 4% 

7% 

Livestock 

5% 

Source: Bloomberg. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse has not sought to 

independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 

Energy 

68% 


Slide 29

Correlation 

Potential Hedge Against Unexpected Inflation 

� Commodity prices have historically tended to rise in line with increased demand for goods and services. 

� Commodities typically exhibit positive returns and relatively low correlations to traditional assets in periods 

of both low and high inflation. 

� Long term inflation may be difficult to predict. 

Correlation in inflation and unexpected 

inflation environm ents 

(January 1970 – Decem ber 2011) 

Inflation 

0.5 

0.4 

0.3 

0.2 

0.1 

0.0 

-0.1 

-0.2 

-0.3 

-0.4 

0.33 

-0.16 

S&P GSCI TR Ibbotson 

Intermediate 

Term Bond 

-0.10 

0.40 

Unexpected Inflation* 

S&P 500 S&P GSCI TR 

-0.35 

Ibbotson 

Intermediate 

Term Bond 

-0.17 

S&P 500 

Average m onthly perform ance in higher and 

lower than expected inflation environm ents 

(January 1970 – Decem ber 2011) 


Lower than Expected Inflation Higher than Expected Inflation 

1.55 

Source: Ibbotson, Bloomberg LLC, Credit Suisse Asset Management, LLC. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit 

Suisse has not sought to independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. 

* Ibbotson Intermediate Term Bond returns represent the Ibbotson Intermediate-Term Government Bond Index TR from 1/1/1970 to 12/31/2010, and BofA Merrill Lynch U.S. Treasury Current 5 Year Index from 

12/31/2010 through the end of the period. 

** Unexpected inflation is based on the historical relationship between 1 month Treasury bills and CPI (Consumer Price Index). See Definitions in back for additional information on asset class descriptions. 

Average Monthly Returns (%) 

1.80 

1.60 

1.40 

1.20 

1.00 

0.80 

0.60 

0.40 

0.20 

0.00 

0.28 

0.84 

S&P GSCI TR Ibbotson 

Intermediate 

Term Bond 

1.36 

S&P 500 S&P GSCI TR Ibbotson 

Intermediate 

Term Bond 

0.50 0.45 

S&P 500 


Slide 30

Commodity Exposures – Index Choices 

� DJ-UBS TR and S&P GSCI TR demonstrate 

similar returns and diversification benefits 

� S&P GSCI TR generally more volatile than DJ- 

% Total Return 

UBS TR 

S&P GSCI TR and DJ-UBS Com m odity Index TR 

80% 

60% 

40% 

20% 

0% 

-20% 

-40% 

1970 

1971 

1972 

1973 

1974 

1975 

1976 

1977 

1978 

1979 

1980 

1981 

1982 

1983 

1984 

1985 

1986 

1987 

1988 

1989 

S&P GSCI TR DJ-UBS TR 


Source: Credit Suisse Asset Management, LLC; Ibbotson; Bloomberg. All data was obtained from publicly available information, internally developed data and other third party sources believed to be reliable. Credit Suisse 

has not sought to independently verify information obtained from public and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. See Definitions in 

back for additional information on asset class descriptions. 

* Returns represent the Ibbotson Intermediate-Term Government Bond Index TR from 1/1/1970 to 12/31/2010, and BofA Merrill Lynch U.S. Treasury Current 5 Year Index from 12/31/2010 through the end of the period. 

1990 

1/ 91 – 

12/ 11 

Return 

(annualized) 

1991 

1992 

1993 

1994 

1995 

DJ-UBS 

TR 

1996 

1997 

1998 

S&P 

GSCI TR 

1999 

2000 

2001 

2002 

International 

Stocks 

Source: Credit Suisse Asset Management, LLC; Ibbotson; Bloomberg. 

2003 

2004 

2005 

2006 

US 

Stocks 

2007 

2008 


Slide 31 

2009 

2010 

US Fixed 

Incom e* 

5.07% 3.46% 5.29% 8.79% 6.68% 

Volatility 15.04% 21.22% 17.00% 15.08% 4.53% 

Correlation 

to DJ-UBS 

Correlation 

to GSCI 

1.00 0.90 0.42 0.30 -0.05 

0.90 1.00 0.34 0.23 -0.06 

2011

Enhanced Commodities Composite – S&P GSCI 

As of October 31, 2012 

2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 

Enhanced Com m odities Index (Gross) -2.09% 9.20% 16.6% -45.7% 34.3% -14.8% 27.1% 18.5% 20.9% 32.6% -32.0% 

Enhanced Com m odities Index (Net) -2.30% 8.77% 16.0% -45.9% 33.8% -15.1% 26.6% 18.1% 20.6% 32.3% -32.2% 

S&P GSCI Total Return Index -1.18% 9.03% 13.5% -46.5% 32.7% -15.1% 25.6% 17.3% 20.7% 32.1% -31.9% 

S&P GSCI Total Return Index less Swap Cost -1.32% 8.86% 13.3% -46.6% 32.4% -15.5% 24.9% 16.5% 19.8% 31.0% -32.6% 

Excess returns (Gross) vs. S&P GSCI less 

Swap 

Annualized Returns 

Oct ’12 YTD 1 Year 3 Year 5 year 7 Year 10 Year 

-0.76% 0.34% 3.30% 0.90% 1.90% 0.70% 2.20% 2.0% 1.1% 1.60% 0.60% 

Excess returns (Net) vs. S&P GSCI less Swap -0.97% -0.09% 2.70% 0.70% 1.40% 0.40% 1.70% 1.60% 0.80% 1.30% 0.40% 

*Inception date of composite: June 1, 1996. All performance figures of greater than a one year period are annualized. 

Please see “Important Legal Information” at the end of this material for important disclosures regarding the data and information contained and the views and opinions expressed in this material. The disclosures are an integral part 

of this presentation. This information presented is supplemental to a GIPS -compliant presentation, which is included in the appendix to this material. For illustrative and informational purposes only. Indices are not subject to 

management fees and are not available for direct investment. Target allocations are subject to change. There is no assurance that the target allocations will be achieved for a client’s portfolio, and actual allocations may be 

significantly different than that shown here. Characteristics and performance of individual client accounts will vary. Investing entails risks, including possible loss of principal. Commodity markets are highly volatile. The risk of loss in 

trading commodities can be substantial. There is a high degree of leverage in commodity trading that can lead to large losses. The investment views of Credit Suisse Asset Management, LLC may change at any time without 

notice. The S&P Goldman Sachs Commodities Index is a composite index of commodity sector returns, representing an unleveraged, long-only investment in commodity futures that is broadly diversified across the spectrum of 

commodities. The returns are calculated on a fully collateralized basis with full reinvestment. The combination of these attributes provides investors with a representative and realistic picture of realizable returns attainable in the 

commodities markets. S&P Goldman Sachs Commodities Index is a trademark of The McGraw-Hill Companies, Inc. and have been licensed for use by Goldman, Sachs & Co. Investors cannot invest directly in an index. Past 

performance is no guarantee of future results. The data presented are based on performance figures which have not been checked fully on account of the annual verification cycle. 


Slide 32 

Since 

Inception* 

Enhanced Com m odities Index (Gross) -3.90% -0.25% -0.51% 3.12% -7.17% -3.70% 4.32% 3.15% 

Enhanced Com m odities Index (Net) -3.90% -0.40% -0.66% 2.84% -7.50% -4.06% 3.94% 2.82% 

S&P GSCI Total Return Index -4.07% -0.74% -1.45% 3.08% -7.93% -4.52% 3.48% 2.79% 

S&P GSCI Total Return Index less Swap 

Cost 

Excess returns (Gross) vs. S&P GSCI less 

Swap 

Excess returns (Net) vs. S&P GSCI less 

Swap 

-4.08% -0.86% -1.60% 2.92% -8.07% -4.72% 3.13% 2.13% 

0.18% 0.61% 1.09% 0.20% 0.91% 1.02% 1.19% 1.02% 

0.18% 0.47% 0.94% -0.09% 0.58% 0.66% 0.81% 0.69%

Enhanced Commodities Composite – DJ-UBS Futures Based 


Enhanced Com m odities Index 

(Gross) 

*Inception date of composite: February 1, 2007 

Oct ’12 YTD 1 Year 3 Year 5 Year 7 Year 10 Year 

Enhanced Commodities Composite – DJ-UBS (Swaps Based) 

Since 

Inception * 

-3.81% 2.60% -3.33% 3.23% -4.13% N/A N/A -1.10% 

Enhanced Com m odities Index (Net) -3.82% 2.34% -3.63% 2.90% -4.37% N/A N/A -1.34% 

DJ-UBS Total Return Index -3.87% 1.54% -4.44% 2.77% -4.43% N/A N/A -1.58% 

Excess returns (Gross) vs. DJ-UBS 0.06% 1.06% 1.10% 0.46% 0.30% N/A N/A 0.48% 

Excess returns (Net) vs. DJ-UBS 0.05% 0.80% 0.81% 0.13% 0.05% N/A N/A 0.23% 




Oct ’12 YTD 1 Year 3 Year 5 Year 7 Year 10 Year 

Since 

Inception * 

Enhanced Commodities Index (Gross) -3.89% 1.17% -4.50% 3.65% -3.55% 0.33% N/A 2.32% 

Enhanced Com m odities Index (Net) -3.96% 0.46% -5.31% 2.81% -4.32% -0.52% N/A 1.44% 

DJ-UBS Total Return Index -3.87% 1.54% -4.44% 2.77% -4.43% -0.50% N/A 1.61% 

Excess returns (Gross) vs. DJ-UBS -0.02% -0.37% -0.07% 0.88% 0.88% 0.82% N/A 0.71% 

Excess returns (Net) vs. DJ-UBS -0.09% -1.08% -0.88% 0.04% 0.10% -0.02% N/A -0.16% 

*Inception date of composite: January 1, 2005. All performance figures of greater than a one year period are annualized. 

Please see “Important Legal Information” at the end of this material for important disclosures regarding the data and information contained and the views and opinions expressed in this material. The disclosures are an 

integral part of this presentation. This information presented is supplemental to a GIPS -compliant presentation, which is included in the appendix to this material. For illustrative and informational purposes only. Indices 

are not subject to management fees and are not available for direct investment. Target allocations are subject to change. There is no assurance that the target allocations will be achieved for a client’s portfolio, and 

actual allocations may be significantly different than that shown here. Characteristics and performance of individual client accounts will vary. Investing entails risks, including possible loss of principal. Commodity 

markets are highly volatile. The risk of loss in trading commodities can be substantial. There is a high degree of leverage in commodity trading that can lead to large losses. The investment views of Credit Suisse Asset 

Management, LLC may change at any time without notice. The Dow Jones – UBS Index is composed of futures contracts on 19 physical commodities. Past performance is no guarantee of future results.The data 

presented are based on performance figures which have not been checked fully on account of the annual verification cycle. 


Slide 33


Schedule of Composite Performance Results 

Enhanced Commodities Index – GSCI Composite 

(Formerly CSAM Total Commodity Return Composite) 

Period from June 1, 1996 through December 31, 2010 

Net 

Total 

Return 

GSCI Total 

Return Index less 

swap cost* 

Gross Total 

GSCI Total 

Number of 

Composite Market Total Firm Assets 

Year 

Return 

Return Index* 

Portfolios Dispersion Value (USD millions) # (USD Millions) 

2010^ 9.20% 8.77% 9.03% 8.86% 3 N/M $102 $14,617 0.70% 

2009^ 16.60 15.98 13.48 13.32 3 N/M 54 27,902 0.19 

2008^ -45.68 -45.92 -46.49 -46.57 3 N/M 40 38.022 0.11 

2007 34.32 33.82 32.68 32.35 3 N/M 116 55,231 0.21 

2006 -14.79 -15.12 -15.10 -15.54 3 N/M 77 125,466 0.07 

2005 27.10 26.54 25.55 24.88 2 N/M 88 52,572 0.17 

2004 18.46 18.07 17.28 16.52 2 N/M 65 24,026 0.27 

2003 20.89 20.61 20.72 19.83 1 N/M 42 46,638 0.09 

2002 32.62 32.30 32.07 30.98 1 N/M 37 48,414 0.08 

2001 -31.99 -32.16 -31.93 -32.59 1 N/M 28 71,165 0.04 

2000 48.48 48.13 49.74 48.26 2 N/M 129 83,360 0.15 

1999 40.13 39.76 40.92 39.39 3 N/M 174 68,508 0.25 

1998 -36.05 -36.23 -35.75 -36.55 2 N/M 52 35,916 0.15 

1997 -14.44 -14.66 -14.08 -15.21 2 N/M 62 25,761 0.24 

1996** 15.12 15.01 15.41 14.47 1 N/M 24 22,610 0.11 

Credit Suisse Asset Management, LLC has prepared and presented this report in compliance with the Global Investment Performance Standards (GIPS®). The CFA Institute has not been involved in the preparation or review of this report. 

Percent of Firm 

Assets 

Note: For the period from June 1, 1996 through December 31, 2000, total returns and data are not covered by KPMG LLP’s Independent Accountants’ Report. Returns and data were verified by other independent accountants. Reports are available upon request. 

* The Goldman Sachs Total Return Commodity Index (GSCI Total Return Index) and the GSCI Total Return Index less Swap Cost have been taken from a published source and have not been examined by KPMG LLP. See note 6. 

** For the period from June 1, 1996 through December 31, 1996. 

# For the period from June 1, 1996 through December 31, 1996 and the years 1997 through 2000, an independent accountant has not examined Total Firm Assets. 

^ 2008, 2009, 2010 data has not been verified by an independent accountant. 

N/M A measure of dispersion may not be meaningful for composites consisting of five or fewer accounts and/or for periods of less than a full year. 

Notes 

1. Credit Suisse Asset Management, LLC (the “Firm” or “Credit Suisse”) is the continuation of Credit Suisse Asset Management (which was renamed from BEA Associates (“BEA”) in January 1999), resulting from the July 1999 reorganization of the Firm from a New York general partnership to a 

Delaware limited liability company. For performance reporting purposes, the Firm also includes (i) Certain assets of CS First Boston Investment Management Corp., which were acquired by BEA in April 1995; (ii) Assets of Warburg Pincus Asset Management, Inc., which was acquired and 

merged into Credit Suisse in July 1999; (iii) Assets of DLJ Asset Management Group, Inc. (“DLJAMG”), which was acquired and the investment advisory business of which was transferred to Credit Suisse in November 2000. The DLJAMG investment advisory business included assets from DLJ 

Investment Management Corp., which was merged into DLJAMG in December 1999, from the asset management business of First Dominion Capital LLC, which was acquired and merged into DLJAMG in September 2000, and from the fixed income asset management business of Brundage, 

Story and Rose, LLC, which was acquired and merged into DLJAMG in September 2000. DLJAMG was renamed from Wood, Struthers & Winthrop Management Corp. in October 1999; (iv) For periods prior to July 1, 2004, assets of Credit Suisse Capital Inc., which was renamed in March 

2001 from WSW Capital Inc., and was a subsidiary of DLJAMG acquired in November 2000. Effective July 1, 2004, the Firm’s Leveraged Investment Group, Hedge Fund of Funds group and Hedge Fund group were consolidated in Credit Suisse Capital Inc., and Credit Suisse Capital Inc. was 

transferred to the Alternative Capital Division of Credit Suisse First Boston; (v) For the period from June 2, 2003 through June 30, 2004, assets of a joint venture between Credit Suisse and Credit Suisse First Boston International that was engaged in the management of hedge fund investments; 

(vi) For periods prior to June 30, 2003, assets of a private equity fund investment business that was transferred from Credit Suisse to Credit Suisse First Boston on that date; and (vii) Assets of DLJ Winthrop Trust Company (Cayman) Ltd., DLJ Winthrop Trust Company (Jersey) Ltd. and 

Winthrop Trust Company. Each of these trust companies was a subsidiary of DLJAMG acquired in November 2000. DLJ Winthrop Trust Company (Cayman) Ltd. was liquidated in November 2003. Total firm assets presented for years prior to 1999 include only those assets of BEA. 

2. Portfolios meeting the stated composite criteria are included in that respective composite in the first full month in which that portfolio is under management. Conversely, portfolios not meeting the stated composite criteria are excluded from that respective composite as of the 1st day following the 

last full measurement period that the portfolio was under management. The Enhanced Commodities Index - GSCI Composite (formerly CSAM Total Commodity Return Composite) includes all discretionary, separately managed, institutional commodity portfolios and mutual funds over 

$5,000,000 that invests in GSCI futures and the underlying commodity contracts (i.e. crude oil, wheat, gold, etc.) to gain exposure to commodities. In addition, the underlying cash collateral is invested in short term U.S. Treasury Bills, commercial paper and other government/agency securities. 

The inception date and creation date of this composite were June 1, 1996 and October 31, 2002 respectively. 

3. The composite results are time-weighted rates of rates of return net of commissions and transactions costs, and have been presented both gross and net of investment advisory fees. Credit Suisse values all portfolios daily and records all transactions on a trade-date basis. Monthly portfolio 

returns are calculated using a time-weighted rate of return. Contributions into portfolios are subtracted from, and withdrawals from accounts are added to the day’s market value minus the previous day’s market value in order to determine the numerator in the daily time-weighted rate of return 

calculation. The prior day’s market value is the denominator and the monthly return is then calculated by compounded multiplication. Monthly composite returns are calculated by weighting each account’s monthly return by its beginning market value as a percent of the total composite beginning 

market value. Annual composite returns are calculated by linking the monthly returns through compounded multiplication. For each portfolio in the composite, net of fee rates of return are calculated by taking the actual quarterly advisory fee as a percentage of the account’s average fee basis for 

the period and is compounded with the gross return to get the net-of-fee return. A composite may include one or more mutual funds, for which the Net Asset Value Returns are adjusted by extracting annual management fees. Performance on this composite has been calculated using U.S. 

dollars. Past performance is no guarantee of future results. 

4. Standard deviation of the Composite performance over time is a measure of dispersion and is calculated using the equal-weighted standard deviation of all portfolios that were included in the composite for the entire year. The calculation measures the fluctuation of the annual rate of return of the 

individual portfolios within the Composite in relation to the average return. Standard deviation is calculated gross of investment management fee and only for composites with greater than five portfolios active for a complete year. 

5. The standard fees charged, on an annual basis, by Credit Suisse applicable to this composite are 0.40% on the first $50 million, 0.35% on the next $100 million, and 0.30% on amounts over $150 million of assets at market value. The minimum fee is $100,000. Fees may be negotiated in lieu of 

the standard fee schedule. Mutual fund fees may be higher than the standard fee schedule. Certain portfolios, which are co-managed with other Credit Suisse affiliates may apply a model fee (based on the highest fee) to calculate net of fee rates of return. There are no non-fee paying portfolios 

in this composite. A schedule of investment advisory fees is contained in Part II of Form ADV on file with the SEC and is available upon request. 

6. The benchmarks for this composite are the Goldman Sachs Total Return Commodity Index (GSCI Total Return Index) and the GSCI Total Return Index less Swap Cost. The GSCI Total Return Index is a composite index of commodity sector returns, representing an unleveraged, long-only 

investment in commodity futures that is broadly diversified across the spectrum of commodities. The returns are calculated on a fully-collateralized basis with full reinvestment. The GSCI Total Return Index less Swap Cost represents the same returns as the GSCI Total Return Index adjusted for 

costs associated with swap transactions. 

7. A complete list and description of all of the Firm’s composites is available upon request. 


Slide 34



Enhanced Commodities Index – DJUBS Future-based Composite 

Period from February 1, 2007 through December 31, 2010 

Gross 

Total 

Return 

Net 

Total 

Return 

Dow Jones UBS 

Commodity Total 

Return Index 

Composite 

Market Value 

(USD millions) 

Total Firm 

Assets # (USD 

millions) 

Percent 

of Firm 

Assets 

Year 


Portfolios Dispersion 

2010^ 17.34% 17.18% 16.83% 3 N/M $644 $14,617 4.41% 

2009^ 21.41% 21.24% 18.91% 3 N/M 534 27,674 1.91% 

2008^ -36.17% -36.26% -35.65% 1 N/M 259 38,022 0.68% 

2007# 16.39% 16.22% 15.99% 2 N/M 395 55,231 0.72% 


# Period from February 1, 2007 through December 31, 2007. 

* The Dow Jones UBS Commodity Total Return Index has been taken from a published source and has not been examined by KPMG LLP. See note 6 below. 


^ 2008 and 2009 data has not been verified by an independent accountant. 

Notes: 

1. Credit Suisse Asset Management, LLC (the “Firm” or “Credit Suisse”) is the continuation of Credit Suisse Asset Management (which was renamed from BEA Associates (“BEA”) in January 1999), resulting from the July 1999 reorganization 

of the Firm from a New York general partnership to a Delaware limited liability company. For performance reporting purposes, the Firm also includes (i) Certain assets of CS First Boston Investment Management Corp., which were acquired by 

BEA in April 1995; (ii) Assets of Warburg Pincus Asset Management, Inc., which was acquired and merged into Credit Suisse in July 1999; (iii) Assets of DLJ Asset Management Group, Inc. (“DLJAMG”), which was acquired and the 

investment advisory business of which was transferred to Credit Suisse in November 2000. The DLJAMG investment advisory business included assets from DLJ Investment Management Corp., which was merged into DLJAMG in December 

1999, from the asset management business of First Dominion Capital LLC, which was acquired and merged into DLJAMG in September 2000, and from the fixed income asset management business of Brundage, Story and Rose, LLC, which 

was acquired and merged into DLJAMG in September 2000. DLJAMG was renamed from Wood, Struthers & Winthrop Management Corp. in October 1999; (iv) For periods prior to July 1, 2004, assets of Credit Suisse Capital Inc., which 

was renamed in March 2001 from WSW Capital Inc., and was a subsidiary of DLJAMG acquired in November 2000. Effective July 1, 2004, the Firm’s Leveraged Investment Group, Hedge Fund of Funds group and Hedge Fund group were 

consolidated in Credit Suisse Capital Inc., and Credit Suisse Capital Inc. was transferred to the Alternative Capital Division of Credit Suisse First Boston; (v) For the period from June 2, 2003 through June 30, 2004, assets of a joint venture 

between Credit Suisse and Credit Suisse First Boston International that was engaged in the management of hedge fund investments; (vi) For periods prior to June 30, 2003, assets of a private equity fund investment business that was 

transferred from Credit Suisse to Credit Suisse First Boston on that date; and (vii) Assets of DLJ Winthrop Trust Company (Cayman) Ltd., DLJ Winthrop Trust Company (Jersey) Ltd. and Winthrop Trust Company. Each of these trust 

companies was a subsidiary of DLJAMG acquired in November 2000. DLJ Winthrop Trust Company (Cayman) Ltd. was liquidated in November 2003. 

2. Portfolios meeting the stated composite criteria are included in that respective composite in the first full month in which that portfolio is under management. Conversely, portfolios not meeting the stated composite criteria are excluded from 

that respective composite as of the 1st day following the last full measurement period that the portfolio was under management. The strategy seeks total return and is designed to exceed the performance of the Dow Jones-UBS Commodity 

Index. It includes portfolios with over $5,000,000 that invest in futures to gain exposure to the DJ UBS in an enhanced index manner as well as commingled vehicles. The futures are backed by a portfolio of short-maturity investment-grade 

fixed income securities normally having an average duration of one year or less. In addition, the underlying cash collateral is invested in short term U.S. Treasury Bills, commercial paper, and other government/agency securities. The composite 

returns are benchmarked against the Dow Jones UBS Commodity Total Return Index. The inception date and creation date of this composite were February 1, 2007 and March 26, 2007, respectively. 

3. The composite results are time-weighted rates of return net of commissions and transactions costs, and have been presented both gross and net of investment advisory fees. Credit Suisse values all portfolios daily and records all 

transactions on a trade-date basis. Monthly portfolio returns are calculated using a time-weighted rate of return. Contributions into portfolios are subtracted from, and withdrawals from accounts are added to the day’s market value minus the 

previous day’s market value in order to determine the numerator in the daily time-weighted rate of return calculation. The prior day’s market value is the denominator and the monthly return is then calculated by compounded multiplication. 

Monthly composite returns are calculated by weighting each account’s monthly return by its beginning market value as a percent of the total composite beginning market value. Annual composite returns are calculated by linking the monthly 

returns through compounded multiplication. For each portfolio in the composite, net of fee rates of return are calculated by taking the actual quarterly advisory fee as a percentage of the account’s average fee basis for the period and is 

compounded with the gross return to get the net-of-fee return. A composite may include one or more mutual funds, for which the Net Asset Value Returns are adjusted by extracting annual management fees. Performance on this composite has 

been calculated using U.S. dollars. Additional information regarding Credit Suisse’s calculation policies is available on request. Past performance is no guarantee of future results. 

4. Standard deviation of the Composite performance over time is a measure of dispersion and is calculated using the equal-weighted standard deviation of all portfolios that were included in the composite for the entire year. The calculation 

measures the fluctuation of the annual rate of return of the individual portfolios within the Composite in relation to the average return. Standard deviation is calculated gross of investment management fee and only for composites with greater 

than five portfolios active for a complete year. 

5. A schedule of investment advisory fees is contained in Part II of Form ADV and is available upon request. 

6. The benchmark for this composite is the Dow Jones – UBS Commodity Total Return Index. The index is designed to be a highly liquid and diversified benchmark for commodities as an asset class. The index is composed of futures 

contracts on 19 physical commodities. 


8. An independent auditor has not reviewed these composites. 


Slide 35



Enhanced Commodities Index – DJUBS Composite 

Period from January 1, 2005 through December 31, 2010 

Gross 

Total 

Return 

Dow Jones UBS 

Commodity Total 

Return Index 

Composite 

Market Value 

(USD millions) 

Total Firm 

Assets # (USD 

millions) 

Percent 

of Firm 

Assets 

Net Total 


Year 

Return 

Portfolios Dispersion 

2010^ 17.74% 16.86% 16.83% 2 N/M $4,697 $14,617 32.13% 

2009^ 20.93% 20.02% 18.91% 2 N/M 2,600 27,902 9.32% 

2008^ -34.82% -35.36% -35.65% 2 N/M 1,073 38,022 2.23% 

2007 15.91% 14.88% 16.23% 2 N/M 935 55,231 1.69% 

2006 2.77% 1.79% 2.08% 2 N/M 577 125,496 0.46% 

2005 21.07% 19.94% 21.35% 1 N/M 170 52,572 0.32% 


# Period from February 1, 2007 through December 31, 2007. 

* The Dow Jones UBS Commodity Total Return Index has been taken from a published source and has not been examined by KPMG LLP. See note 6 below. 


^ 2008, 2009, 2010 data has not been verified by an independent accountant. 

Notes: 

1. Credit Suisse Asset Management, LLC (the “Firm” or “Credit Suisse”) is the continuation of Credit Suisse Asset Management (which was renamed from BEA Associates (“BEA”) in January 1999), resulting from the July 1999 reorganization 

of the Firm from a New York general partnership to a Delaware limited liability company. For performance reporting purposes, the Firm also includes (i) Certain assets of CS First Boston Investment Management Corp., which were acquired by 

BEA in April 1995; (ii) Assets of Warburg Pincus Asset Management, Inc., which was acquired and merged into Credit Suisse in July 1999; (iii) Assets of DLJ Asset Management Group, Inc. (“DLJAMG”), which was acquired and the 

investment advisory business of which was transferred to Credit Suisse in November 2000. The DLJAMG investment advisory business included assets from DLJ Investment Management Corp., which was merged into DLJAMG in December 

1999, from the asset management business of First Dominion Capital LLC, which was acquired and merged into DLJAMG in September 2000, and from the fixed income asset management business of Brundage, Story and Rose, LLC, which 

was acquired and merged into DLJAMG in September 2000. DLJAMG was renamed from Wood, Struthers & Winthrop Management Corp. in October 1999; (iv) For periods prior to July 1, 2004, assets of Credit Suisse Capital Inc., which was 

renamed in March 2001 from WSW Capital Inc., and was a subsidiary of DLJAMG acquired in November 2000. Effective July 1, 2004, the Firm’s Leveraged Investment Group, Hedge Fund of Funds group and Hedge Fund group were 

consolidated in Credit Suisse Capital Inc., and Credit Suisse Capital Inc. was transferred to the Alternative Capital Division of Credit Suisse First Boston; (v) For the period from June 2, 2003 through June 30, 2004, assets of a joint venture 

between Credit Suisse and Credit Suisse First Boston International that was engaged in the management of hedge fund investments; (vi) For periods prior to June 30, 2003, assets of a private equity fund investment business that was 

transferred from Credit Suisse to Credit Suisse First Boston on that date; and (vii) Assets of DLJ Winthrop Trust Company (Cayman) Ltd., DLJ Winthrop Trust Company (Jersey) Ltd. and Winthrop Trust Company. Each of these trust 

companies was a subsidiary of DLJAMG acquired in November 2000. DLJ Winthrop Trust Company (Cayman) Ltd. was liquidated in November 2003. 

2. Portfolios meeting the stated composite criteria are included in that respective composite in the first full month in which that portfolio is under management. Conversely, portfolios not meeting the stated composite criteria are excluded from 

that respective composite as of the 1st day following the last full measurement period that the portfolio was under management. The Enhanced Commodities Index – DJUBS Composite includes all discretionary, separately managed, institutional 

commodity portfolios and mutual funds. The strategy seeks total return and is designed to exceed the performance of the Dow Jones-UBS Commodity Index. The product invests in commodity-linked derivative instruments backed by a portfolio 

of short-maturity investment-grade fixed income securities normally having an average duration of one year or less. The inception date and creation date of this composite were January 1, 2005 and December 30, 2004, respectively. 

3. The composite results are time-weighted rates of return net of commissions and transactions costs, and have been presented both gross and net of investment advisory fees. Credit Suisse values all portfolios daily and records all transactions 

on a trade-date basis. Monthly portfolio returns are calculated using a time-weighted rate of return. Contributions into portfolios are subtracted from, and withdrawals from accounts are added to the day’s market value minus the previous day’s 

market value in order to determine the numerator in the daily time-weighted rate of return calculation. The prior day’s market value is the denominator and the monthly return is then calculated by compounded multiplication. Monthly composite 

returns are calculated by weighting each account’s monthly return by its beginning market value as a percent of the total composite beginning market value. Annual composite returns are calculated by linking the monthly returns through 

compounded multiplication. For each portfolio in the composite, net of fee rates of return are calculated by taking the actual quarterly advisory fee as a percentage of the account’s average fee basis for the period and is compounded with the 

gross return to get the net-of-fee return. A composite may include one or more mutual funds, for which the Net Asset Value Returns are adjusted by extracting annual management fees. Performance on this composite has been calculated using 

U.S. dollars. Additional information regarding Credit Suisse’s calculation policies is available on request. Past performance is no guarantee of future results. 

4. Standard deviation of the Composite performance over time is a measure of dispersion and is calculated using the equal-weighted standard deviation of all portfolios that were included in the composite for the entire year. The calculation 

measures the fluctuation of the annual rate of return of the individual portfolios within the Composite in relation to the average return. Standard deviation is calculated gross of investment management fee and only for composites with greater 

than five portfolios active for a complete year. 

5. The standard fees charged, on an annual basis, by Credit Suisse applicable to this composite are 0.40% on the first $50 million, 0.35% on the next $100 million, and 0.30% on amounts over $150 million of assets at market value. The 

minimum fee is $100,000. Fees may be negotiated in lieu of the standard fee schedule. Mutual fund fees may be higher than the standard fee schedule. Certain portfolios, which are co-managed with other Credit Suisse affiliates may apply a 

model fee (based on the highest fee) to calculate net of fee rates of return. There are no non-fee paying portfolios in this composite. A schedule of investment advisory fees I contained in Part II of Form ADV and is available upon request. 

6. The benchmark for this composite is the Dow Jones – UBS Commodity Total Return Index. The index is designed to be a highly liquid and diversified benchmark for commodities as an asset class. The index is composed of futures contracts 

on 19 physical commodities. 



Slide 36

4. Important Legal Information 


Slide 37

Important Legal Information 

� Important Inform ation Regarding Hypothetical, Back-Tested or Sim ulated Perform ance: 

� Hypothetical back-tested perform ance shown is for illustrative purposes only and does not represent actual perform ance of any client 

account. Credit Suisse Asset Management, LLC (“Credit Suisse”) did not manage any accounts using the portfolio composition for the periods shown 

and does not represent that the hypothetical returns would be similar to actual performance had the firm actually managed accounts in this manner. 

� Hypothetical, back-tested or simulated perform ances have m any inherent limitations only some of which are described as follows: (i) It is 

designed with the benefit of hindsight, based on historical data, and does not reflect the impact that certain economic and market factors might have had 

on the decision-making process. No hypothetical, back-tested or simulated performance can completely account for the impact of financial risk in actual 

performance. Therefore, it will invariably show positive rates of return. (ii) It does not reflect actual client asset trading and cannot accurately account 

for the impact of financial risk or the ability to withstand losses. (iii) The information is based, in part, on hypothetical assumptions made for modeling 

purposes that may not be realized in the actual management of accounts. No representation or warranty is made as to the reasonableness of the 

assumptions made or that all assumptions used in achieving the returns have been stated or fully considered. Assumption changes may have a material 

impact on the model returns presented. This material is not representative of any particular client’s experience. Investors should not assum e that they 

will have an investm ent experience sim ilar to the hypothetical, back-tested or sim ulated perform ance shown. There are frequently material 

differences between hypothetical, back-tested or simulated performance results and actual results subsequently achieved by any investment strategy. 

� Unlike an actual performance record based on trading actual client portfolios, hypothetical, back-tested or simulated results are achieved by means of the 

retroactive application of a back-tested model itself designed with the benefit of hindsight. Hypothetical, back-tested or simulated performance does not 

reflect the impact that material economic or market factors might have on an adviser's decision making process if the adviser were actually managing a 

client’s portfolio. The back-testing of performance differs from actual account performance because the investment strategy may be adjusted at any time, 

for any reason and can continue to be changed until desired or better performance results are achieved. The back-tested performance includes 

hypothetical results that do not reflect the reinvestment of dividends and other earnings or the deduction of advisory fees, brokerage or other commissions, 

and any other expenses that a client would have paid or actually paid. No representation is m ade that any account will or is likely to achieve profits 

or losses sim ilar to those shown. Alternative modeling techniques or assumptions might produce significantly different results and prove to be more 

appropriate. Past hypothetical, back-test or simulated results are neither indicators nor guarantees of future returns. In fact, there are frequently sharp 

differences between hypothetical, back-tested and simulated performance results and the actual results subsequently achieved. As a 

sophisticated investor, you accept and agree to use such information only for the purpose of discussing with Credit Suisse your preliminary interest in 

investing in the strategy described herein. 


Slide 38

Important Legal Information 

� This material has been prepared by Credit Suisse Asset Management, LLC (“Credit Suisse”) on the basis of publicly available information, internally 

developed data and other third party sources believed to be reliable. Credit Suisse has not sought to independently verify information obtained from public 

and third party sources and makes no representations or warranties as to accuracy, completeness or reliability of such information. All opinions and views 

constitute judgments as of the date of writing without regard to the date on which the reader may receive or access the information, and are subject to 

change at any time without notice and with no obligation to update. This material is for informational and illustrative purposes only and is intended solely for 

the information of those to whom it is distributed by Credit Suisse. No part of this material may be reproduced or retransmitted in any manner without the 

prior written permission of Credit Suisse. Credit Suisse does not represent, warrant or guarantee that this information is suitable for any investment 

purpose other than as specifically contemplated by a written agreement with Credit Suisse and it should not be used as a basis for investment decisions. 

This material does not purport to contain all of the information that a prospective investor may wish to consider. This material is not to be relied upon as 

such or used in substitution for the exercise of independent judgment. Past perform ance does not guarantee or indicate future results. 

� This material should not be viewed as a current or past recommendation or a solicitation of an offer to buy or sell any securities or investment products or 

to adopt any investment strategy. The securities identified and described do not represent all of the securities purchased, sold or recommended for client 

accounts. The reader should not assume that any investments in companies, securities, sectors, strategies and/or markets identified or described herein 

were or will be profitable and no representation is made that any investor will or is likely to achieve results comparable to those shown or will make any 

profit or will be able to avoid incurring substantial losses. This informational report does not constitute research and may not be used or relied upon in 

connection with any offer or sale of a security or hedge fund or fund of hedge funds. Performance differences for certain investors may occur due to 

various factors, including timing of investment and eligibility to participate in new issues. Investment return will fluctuate and may be volatile, especially over 

short time horizons. A complete list of investments for the preceding year is available upon request. Each investor’s portfolio may be individually managed 

and may vary from the information shown in terms of portfolio holdings, characteristics and performance. Current and future portfolio compositions may be 

significantly different from the information shown herein. Investing entails risks, including possible loss of som e or all of the investor’s principal. 

The investment views and market opinions/analyses expressed herein may not reflect those of Credit Suisse Group AG as a whole and different views may 

be expressed based on different investment styles, objectives, views or philosophies. To the extent that these materials contain statements about the future, 

such statements are forward looking and are subject to a number of risks and uncertainties. 

� The only legally binding terms of this investment product including risk considerations, objectives, charges and expenses are set forth in the private 

placement memorandum and subscription documents which are available upon request. This document does not constitute an offer or invitation to enter 

into any type of financial transaction. The issuer has no obligation to issue this investment product. Where not explicitly otherwise stated, the issuer has no 

duty to invest in the underlying assets. Before deciding to invest, prospective investors must carefully read the relevant private placement memorandum 

and subscription documents and pay particular attention to the risk factors contained therein and determine if this investment product suits the investor’s 

particular circumstances and should independently assess (with the investor’s tax, legal and financial advisers) the specific risks (maximum loss, currency 

risks, etc.) and the legal, regulatory, credit, tax and accounting consequences. Prospective investors should have the financial ability and willingness to 

accept the risk characteristics of this investment product. This investment product is intended only for investors who understand and are capable of 

assuming all risks involved. Credit Suisse makes no representation as to the suitability of this investment product for any particular investor or as to the 

future performance of this investment product. 


Slide 39

Important Legal Information (cont’d) 

� Investm ents in hedge funds are speculative and involve a high degree of risk. Hedge funds may exhibit volatility and investors may lose all or 

substantially all of their investment. A hedge fund manager typically controls trading of the fund and the use of a single advisor’s trading program may result 

in a lack of diversification. Hedge funds also may use leverage and trade on foreign markets, which may carry additional risks. Investments in illiquid 

securities or other illiquid assets and the use of short sales, options, leverage, futures, swaps, and other derivative instruments may create special risks and 

substantially increase the impact of adverse price movements. Hedge funds typically charge higher fees than many other types of investments, which can 

offset trading profits, if any. Interests in hedge funds may be subject to limitations on transferability. Hedge funds are illiquid and no secondary market for 

interests typically exists or is likely to develop. The incentive fee may create an incentive for the hedge fund manager to make investments that are riskier 

than it would otherwise make and such risk-taking may place the interests of the hedge fund manager in conflict with the interests of investors. 

� The charts, tables and graphs contained in this document are not intended to be used to assist the reader in determining which securities to buy or sell or 

when to buy or sell securities. 

� Benchmarks are used solely for purposes of comparison and the comparison does not mean that there will necessarily be a correlation between the 

returns described herein and the benchmarks. There are limitations in using financial indices for comparison purposes because, among other reasons, 

such indices may have different volatility, diversification, credit and other material characteristics (such as number or type of instrument or security). 

� Credit Suisse Asset Management, LLC is part of Credit Suisse’s asset management business. The asset management business of Credit Suisse is 

comprised of a network of global entities with offices in 23 countries around the world. Each legal entity is subject to distinct regulatory requirements and 

certain asset management products and services may not be available in all jurisdictions or to all client types. Information herein may refer to Credit Suisse 

and its global affiliates. There is no intention to offer products and services in countries or jurisdictions where such offer would be unlawful under the 

relevant domestic law. 

� Certain risks relating to investing in Commodities and Commodity-Linked Investments: Exposure to commodity markets should only form a small 

part of a diversified portfolio. Investment in commodity markets may not be suitable for all investors. Commodity investments will be affected by changes in 

overall market movements, commodity volatility, exchange-rate movements, changes in interest rates, and factors affecting a particular industry or 

commodity, such as drought, floods, weather, livestock disease, embargoes, tariffs and international economic, political and regulatory developments. 

Commodity markets are highly volatile. The risk of loss in commodities and commodity-linked investments can be substantial. There is generally a high 

degree of leverage in commodity investing that can significantly magnify losses. Gains or losses from speculative derivative positions may be much greater 

than the derivative’s original cost. 

� Inform ation related to GIPS ® Com pliance: The firm as defined by the GIPS® Standards consists of the funds and institutional mandates managed by 

the Asset Management division of CREDIT SUISSE and is in compliance with the GIPS® 2010. The fact of compliance is verified by an independent 

auditor on an annual basis. Neither the CFA Institute nor any local bankers' associations have been involved in the preparation or review of this 

presentation. 

� Copyright © 2012, Credit Suisse Group AG and/or its affiliates. All rights reserved. 


Slide 40

City of San Jose 

FQ Balanced Risk Commodity 

Handouts 

December 12, 2012

2 

Neutral Weight Difference 

Weight 

40.0% 

35.0% 

30.0% 

25.0% 

20.0% 

15.0% 

10.0% 

5.0% 

0.0% 

18.7% 

17.8% 

21.4% 

Neutral Weight Difference 

CS Risk Parity Benchmark vs. BRC Median Risk 

27.3% 

28.6% 

37.3% 

Energy Agriculture Livestock Base Metals Precious Metals Total Difference 

CS BRC 

17.5% 

12.3% 

13.8% 

22.3% 

16.9% 

City of San Jose

3 

Quarterly Return Attribution 

Return Attribution 

3.0% 

2.0% 

1.0% 

0.0% 

-1.0% 

-2.0% 

-3.0% 

-4.0% 

0.5% 

-0.1% 

1.0% 

0.0% 

0.8% 

Quarterly Return Attribution 

FQ BRC vs. CS Risk Parity Benchmark 

0.7% 

0.2% 

-2.7% 

0.1% 

-0.6% 

-0.7% 

2011Q2 2011Q3 2011Q4 2012Q1 2012Q2 2012Q3 Annual 

0.7% 

-1.5% 

-1.4% 

Pricing Difference Active Neutral Weight Diff 

0.4% 

0.6% 

-1.5% 

-0.6% 

-1.5% 

0.0% 


4 

Relative Sector Attribution 

Relative Sector Returns 

4.0% 

3.0% 

2.0% 

1.0% 

0.0% 

-1.0% 

-2.0% 

-3.0% 

-4.0% 

0.0% 

0.2% 

1.9% 

-1.7% 

0.1% 

0.1% 

0.8% 

1.3% 

0.7% 

0.1% 

BRC vs. CS Balanced Commodity Index 

Relative Sector Performance: 4/11 - 9/12 

-0.5% 

-0.8% 

-0.4% 

-0.1% 

-0.2% 

0.2% 

-1.3% 

-1.6% 

-0.4% 

2011Q2 2011Q3 2011Q4 2012Q1 2012Q2 2012Q3 Annual 

-0.1% 

0.5% 

0.1% 

0.9% 

0.0% 

-0.7% 

Energy Agriculture Livestock Base Metals Precious Metals 

0.7% 

0.5% 

-1.5% 

-0.3% 

-0.7% 

0.6% 

0.6% 

0.5% 

-1.2% 

-2.0% 



December 12, 2012

AUM and performance quoted for the most recent period may be preliminary. Unless 

otherwise noted, performance figures do not reflect the deduction of investment advisory 

fees. These fees are described in Part 2 of our Form ADV, which is available upon request. 

The returns shown will be reduced by the advisory fees and any other expenses the advisor 

may incur in the management of an investment advisory account. This material is for your 

private information. All material has been obtained from sources believed to be reliable, 

but its accuracy is not guaranteed. Past or simulated performance is no guarantee of future 

results. Potential for profit is accompanied by possibility of loss. 

Confidential. For Private Use Only. 

SECTION 01 

Firm Overview 

SECTION 02 

Balanced Risk 

Commodities 

BIOGRAPHIES 


December 12, 2012

Past performance is no guarantee of future results. Potential for profit is accompanied by possibility of loss.

2 

Firm Overview: About First Quadrant 

Founded in 1988 

$17.7 billion Assets Under Management 1 

Headquartered in Pasadena, CA 

Partnership with Employee Ownership 

98 Total Employees 

28 Investment Professionals 

Global, Institutional Client Base 

Systematic, Theory-Based Process 

AMG Partnership Enhances Global Presence 

Client Breakdown 2 

Public 47% 

Corporate 30% 

Joint Venture 6% 

Sub-Advisory 14% 

HNW/Family Office 1% 

Endowment/Foundation 2% 

Investment Professionals: Diverse Backgrounds 

Finance/Business 29% 

Social Science 9% 

Physical Science 17% 

Mathematics 17% 

Engineering 28% 

As of September 2012. Employee information as of October 2012. 

1Includes market values for fully funded portfolios and the notional values for margin funded portfolios, all actively managed by First Quadrant and non-discretionary portfolios managed by joint venture partners using First 

Quadrant, LP investment signals. First Quadrant is defined in this context as the combination of all discretionary portfolios of First Quadrant, LP and its joint venture partners, but only wherein FQ has full investment discretion 

over the portfolios. 2 As of percentage of total actively managed assets.

3 

Our People: Investment Professionals 

October 2012 

Name Industry FQ Education Name 

Industry FQ Education 

Portfolio Management & Research 

¹Partner 

Years Experience 

Matthew Michelson, PhD 2 2 PhD, MS — University of Southern California 

Max Darnell¹ 21 21 MA — University of California, Los Angeles Bruno Miranda, PhD 6 4 PhD, MS — University of California, Los Angeles 

Ken Ferguson, PhD¹ 18 18 PhD — University of Utah Ben Solecki 6 6 BS — California Institute of Technology 

Dori Levanoni¹ 20 20 California Institute of Technology Ian Swanson, PhD 3 3 

PhD — California Institute of Technology 

MFE — University of California, Berkeley 

Edgar Peters¹ 34 4 MBA — Rutgers University Christopher Whelan 1 1 BS — California Institute of Technology 

Jia Ye, PhD¹ 17 17 PhD, MS — University of Southern California Junyao Zhang, CFA 13 13 MS — Washington University, St. Louis 

David Chrisman, PhD, CFA 13 13 PhD — University of California, Los Angeles 

Jesse Davis, CFA 7 4 MEng — Massachusetts Institute of Technology Nhan Bui 21 19 BS — California Polytechnic University, Pomona 

Ghene Faulcon 11 8 MBA — London Business School Byung Kim 18 3 MBA — Cornell University 

Paul Goldwhite, CFA 28 6 BS — Yale University Laurie Morales 29 24 BA — California State Uiniversity, Los Angeles 

Jeppe Ladekarl 18 3 MSc — University of Copenhagen Nihar Panda, CFA 9 2 MS — University of California, Berkeley 

Paul Brennan 13 8 MA — St. Catharine's College, University of Cambridge Tomo Tokuyama 5

4 

Our Strategies: Tools for Building Investment Solutions 

Our ALPHA strategies 

are designed to be truly 

uncorrelated and not 

simply an “excess 

return” 

ALPHA 

GTAA 

Currency 

Global Diversified Alpha 

Commodities Long/Short 

Equity Market Neutral 

TOTAL RETURN 

Essential Beta Total Return 

Commodities Total Return 

Our TOTAL RETURN strategies 

combine best ideas in alpha and 

beta in an effort to achieve higher 

risk-adjusted returns 

BETA 

Essential Beta 

Balanced Risk Commodities 

Long-only Equities 

Extended Equities 

Tax-Advantaged Equities 

Our BETA strategies seek to 

capture only the essential forms 

of beta, balance risk and deliver 

a consistent risk profile

5 

Our Investment Philosophy 

We believe… 

> Behavioral Biases, Structural Imbalances and Volatility Cycles create market 

opportunities 

> The Scientific Method is the best way to identify these opportunities and to 

avoid data mining 

> An Adaptive Investment Process generates differentiated returns by exploiting 

a diverse set of these opportunities 

Our objective is to deliver superior risk-adjusted returns; to achieve this we… 

> Build Breadth 

> Respond Tactically 

> Innovate Relentlessly 

The unique way in which FQ combines these three actions 

separates us from our peers

6 

Our Style: “Quants” with a Human Touch 

We are investors first, “Quants” 

second 

> We are led by “ideas” rather than 

data and we implement 

systematically 

People and discretion play a role 

in our process 

> We constantly monitor for unusual 

or extraordinary circumstances 

and events 

We are adaptive 

> We will react in a transparent and 

systematic manner if we detect 

extreme conditions 

“Investors must always be on guard 

against circumstances that may 

temporarily render their strategies 

irrelevant.” 

–Max Darnell, FQ Perspective, Sept 2007 

Piloting Quantitative Investment Strategies 

“As we have seen in 2007 and 2008, a high 

volatility environment has extreme events 

on both the upside and downside.” 

–Ed Peters, FQ Perspective, Feb 2009 

Balancing Betas – Essential Risk Diversification

7 

Managing Risk from Stage One 

Risk Awareness permeates our culture 

Risk Allocation includes identifying and 

taking risk only where we expect to be 

compensated 

Risk Management is integrated into all 

aspects of our investment process, 

managing risk continuously for the not so 

average day 

Risk Monitoring is a continuous multidimensional 

process, independently 

monitored by the Risk Office

8 

Key Features 

We are a boutique investment firm with over two decades of investment 

expertise 

We employ a systematic, theory-based process, always keeping in mind that 

we are investors first and quants second 

We have a long history of implementing asset allocation and equity strategies 

offering pure alpha, beta and total return solutions 

We view and manage risk from all perspectives from the enterprise level to 

research and post implementation 

We are a stable organization with a strong client focus

AUM and performance quoted for the most recent period may be preliminary. Unless otherwise noted, performance figures do not reflect the deduction of investment 

advisory fees. These fees are described at the end of this presentation. The returns shown will be reduced by the advisory fees and any other expenses the advisor 

may incur in the management of an investment advisory account. This material is for your private information. All material has been obtained from sources believed 

to be reliable, but its accuracy is not guaranteed. 

Past or simulated performance is no guarantee of future results. Potential for profit is accompanied by possibility of loss. 

Commodities trading involves substantial risk of loss. 

FOR ONE-ON-ONE USE ONLY

2 

What Can an Allocation to Commodities Provide? 

Better Inflation Tracking 

> Commodity prices tend to rise during periods of inflation 

> Commodity prices can cause inflation 

> Protection against USD decline 

Diversification to Equity and Fixed Income 

> Commodities can substantially reduce portfolio risk 

> Commodities have low correlation to the broad market 

Participation in Global Economic Growth 

> Increased demand for goods and services, 

may increase prices of those goods and services, 

increasing the price of those commodities used

3 

100% 

Allocating to Commodities: Capital versus Risk 

January 1988 – December 2011 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

71% 

15% 

Capital Allocation Risk Allocation 

4% 7% 

7% 

3% 

20% 

Sources: First Quadrant, LP, Global Financial Data (GFD) 

Capital and risk allocation figures updated on an annual basis as more frequent data updates do not contribute materially to the analysis. 

11% 

33% 

29% 

S&P GSCI DJ UBSCI 

Agriculture Energy 

Precious Metals Industrial Metals Livestock 

100% 

DJ UBSCI: Dow Jones UBS Commodity Index S&P GSCI: S&P Goldman Sachs Commodity Index 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

95% 

2% 

0% 

2% 

0% 

1% 

17% 

4% 

61% 

17% 

S&P GSCI DJ UBSCI

4 

Maximizing Diversification Across Sectors 

Balanced Risk Commodities (BRC) Simulation Sector Returns 

BEST 

RANKED IN ORDER OF PERFORMANCE 

WORST 

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 

19.0% 5.1% 21.4% 27.9% 18.4% 19.8% 37.5% 19.7% 1.7% 57.1% 27.5% 9.0% 

9.6% 1.2% 16.0% 14.6% 18.3% 15.5% 21.7% 19.1% -2.8% 28.7% 22.1% 4.5% 

0.5% -6.5% 11.6% 6.5% 14.9% 13.0% 10.5% 17.0% -3.3% 23.4% 17.4% -5.7% 

-6.3% -7.7% 6.3% 4.7% 10.1% 8.5% -1.4% 2.5% -20.2% 22.7% 10.4% -11.1% 

-6.4% -13.4% 4.3% -0.8% 7.2% -1.7% -3.5% -1.4% -34.5% 3.6% 3.8% -23.2% 


Livestock 

Precious 

Metals 

Industrial 

Metals 


The returns of BRC sectors are shown at 12% risk level. 

Balanced Risk Commodities simulation is supplemental information. Please see Balanced Risk Commodities – Simulated Performance (Gross of Fees) and Balanced Risk Commodities Strategies Composite 

Information and Balanced Risk Commodities Strategy (Gross of Fees) disclosures found at the end of this presentation for information concerning this simulation, the live composite, and the effect of fees on the 

performance. 

First Quadrant Balanced Risk Commodities (“FQ BRC”) is a risk weighted portfolio, consisting of the following commodities, which serve as proxies to sectors presented above: WTI Oil, Brent Oil, Natural Gas, RBOB 

Gasoline, Heating Oil, Wheat, Corn, Soybeans, Coffee, Sugar, Cocoa, Copper, Aluminum, Lead, Zinc, Nickel, Gold, Silver, Live Cattle, Lean Hogs. FQ BRC balances risk across these so that each commodity has an 

equal risk footing in the portfolio.

5 

Balanced Risk Commodities 

Why balance risk? 

> Production based indices are heavily influenced by Energy 

> Production based indices maintain a high degree of idiosyncratic risk 

How does one balance risk? 

> Leverage the low risk sectors 

> Reduce the weight of the high risk sectors 

> Adjust for levels of market volatility 

What can a risk balanced portfolio deliver? 

> A more efficient portfolio 

> An expected Sharpe Ratio that is higher than standard indices 

> A better hedge against inflation over the long run 

> Better participation from all commodity sectors, rather than one or two 

> The same diversification effect with stocks and bonds

6 

How is a Risk Balanced Objective Achieved? 


Risk Allocation 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

20% 

20% 

20% 

20% 

20% 

FQ BRC Simulation S&P GSCI DJ UBSCI 

95% 

2% 

Agriculture Energy Precious Metals Industrial Metals Livestock 

Sources: First Quadrant, LP, StyleAdvisor, Bloomberg LP 

Risk allocation figures updated on an annual basis as more frequent data updates do not contribute materially to the analysis. 



performance. 

First Quadrant Balanced Risk Commodities (“FQ BRC”) is a risk weighted portfolio, consisting of the following commodities, which serve as proxies to sectors presented above: WTI Oil, Brent Oil, Natural Gas, RBOB 

Gasoline, Heating Oil, Wheat, Corn, Soybeans, Coffee, Sugar, Cocoa, Copper, Aluminum, Lead, Zinc, Nickel, Gold, Silver, Live Cattle, Lean Hogs. FQ BRC balances risk across these so that each commodity has an equal 

risk footing in the portfolio. 

0% 

2% 

0% 

17% 

4% 

61% 

17% 

1%

7 

Balancing Risk Through Exchange-Traded Futures: Example Gold and Oil 

Illustrative Example 

Excess Return over 30-Day T-Bills (%) 

8 

7 

6 

5 

4 

3 

2 

1 

0 

Unleveraged: 

19% Oil, 81% Gold 

Leveraged: 

37% Oil, 87% Gold 

1 100% Gold 

0 5 10 15 20 25 30 35 

Figures based on historical empirical data. 

Sources: First Quadrant, LP, Global Financial Data (GFD). Gold is gold futures and Oil is WTI oil futures, constant maturity. Based on monthly rebalancing with zero transaction costs. 

4 

Risk 

5 

3 

50% Oil, 50% Gold 

1 2 3 4 5 

100% Gold 100% Oil 

50% Oil 

50% Gold 

Unleveraged 

Gold (19/81) 

2 

100% Oil 

Leveraged 

Gold (37/87) 

Excess Return 4.1 7.2 5.7 4.7 6.2 

Risk 15.0 33.2 19.7 14.8 19.7 

Sharpe Ratio 0.28 0.22 0.29 0.32 0.32

8 

Building a Balanced Risk Commodity Strategy 

Diversification Across Three Dimensions 

Across Sectors 

LIVESTOCK 

INDUSTRIAL 

METALS 

PRECIOUS 

METALS 

ENERGY 

AGRICULTURE 

��Live Cattle 

��Lean Hogs 

��Copper 

��Aluminum 

��Lead 

��Gold 

��Silver 

Within Sectors 

��WTI Oil 

��Brent Oil 

��Heating Oil 

��Wheat 

��Corn 

��Soybeans 

��Nickel 

��Zinc 

��Natural Gas 

��RBOB Gasoline 

��Coffee 

��Sugar 

��Cocoa 

Through Time 

Volatility Regime Range: (Very Low to Very High) 

Allocation 

48% to 27% 

13% to 11% 

27% to 18% 

26% to 10% 

32% to 23%

9 

Volatility Regimes Impact Asset Allocation 

January 1990 – September 2012 

VIX Levels 

70 

60 

50 

40 

30 

20 

10 

0 

US 

Recession 

VIX = 30 

Bond 

Market 

Sell off 

VIX = 20 

1990 1992 1995 1998 2001 2003 2006 2009 2012 

Sources: Chicago Board Options Exchange, First Quadrant, LP 

Low Volatility High Volatility Low Volatility High Volatility 

Asian 

LTCM 

VIX = 44 9/11 

Market 

Risk 

VIX = 35 

VIX = 34 Iraq War 

Tech 

VIX = 40 

Bubble 

VIX = 30 

Subprime Credit 

Crisis 

VIX = 60 

80 

70 

60 

50 

40 

30 

20 

10 

0

10 

Capital Allocation 

Balancing Commodity Risk through Time: Market Risk Index 

160% 

140% 

120% 

100% 

80% 

60% 

40% 

20% 

0% 

Very Low Risk 

Low Risk 

Median 

High Risk 

Very High Risk 

13% 

32% 

48% 

27% 

26% 

13% 

29% 

43% 

25% 

22% 

12% 

27% 

37% 

22% 

18% 

12% 

25% 

32% 

20% 

14% 

11% 

23% 

27% 

18% 

10% 

Energy Precious Metal Livestock Agriculture Industrial Metals 

Bottom 

Quartile 

Implied 

Volatility 

Lower 

Narrowing 

Very High Risk Regime Allocation includes 12% cash for risk aversion. Cash is comprised of 30 day T-Bills. 

Implied Volatility Higher 

Credit Spreads 

Widening 

Expanding Economic Growth Contracting 

Easing Monetary Policy Tightening 

Top 

Quartile 

Implied 

Volatility

11 

Historical Allocations: Balanced Risk Commodities 

FQ BRC Simulation: January 1988 – September 2012 

Exposure 

160% 

140% 

120% 

100% 

80% 

60% 

40% 

20% 

0% 

1988 1990 1992 1995 1997 2000 2002 2004 2007 2009 2012 

Agriculture Energy Precious Metals Industrial Metals Livestock 



Information and Balanced Risk Commodities Strategy (Gross of Fees) disclosures found at the end of this presentation for information concerning this simulation, the live composite, and the effect of fees on the performance. 

First Quadrant Balanced Risk Commodities (“FQ BRC”) is a risk weighted portfolio, consisting of the following commodities, which serve as proxies to sectors presented above: WTI Oil, Brent Oil, Natural Gas, RBOB Gasoline, 

Heating Oil, Wheat, Corn, Soybeans, Coffee, Sugar, Cocoa, Copper, Aluminum, Lead, Zinc, Nickel, Gold, Silver, Live Cattle, Lean Hogs. FQ BRC balances risk across these so that each commodity has an equal risk footing in 

the portfolio. Very High Risk Regime Allocation includes 12% cash for risk aversion. Cash is comprised of 30 day T-Bills.

12 

Attribution 


12% 

10% 

8% 

6% 

4% 

2% 

0% 

1.8% 

1.4% 

2.7% 

3.0% 

2.0% 

FQ BRC 

Simulation 

Total Return (%) Contribution to Excess Return 1 

6.3% 

0.7% 

0.1% 

0.4% 

0.2% 

0.9% 

0.7% 

3.5% 

1.4% 


0.2% 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

17% 

13% 

25% 

27% 

18% 

FQ BRC 

Simulation 

5% 

3% 

81% 

9% 

2% 3% 

14% 

10% 

53% 

20% 



Precious Metals Industrial Metals Livestock 


Attribution figures updated on an annual basis as more frequent data updates do not contribute materially to the analysis. 



First Quadrant Balanced Risk Commodities (“FQ BRC”) is a risk weighted portfolio, consisting of the following commodities, which serve as proxies to sectors presented above: WTI Oil, Brent Oil, Natural Gas, RBOB Gasoline, 

Heating Oil, Wheat, Corn, Soybeans, Coffee, Sugar, Cocoa, Copper, Aluminum, Lead, Zinc, Nickel, Gold, Silver, Live Cattle, Lean Hogs. FQ BRC balances risk across these so that each commodity has an equal risk footing in 

the portfolio. ¹Excess return is in excess of 30 day T-Bills i.e. cash.

13 

Sharpe Ratio Across Risk Balancing Dimensions 

FQ BRC Simulation: January 1988 – December 2011 

Sharpe Ratio 

0.8 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0.0 

0.1 

DJ UBSCI 

Step 1: Balance 

risk Across sectors 

0.3 

Step 2: Balance risk 

Within each sector 

0.6 

Step 3: Balance risk 

Through risk regimes 


Simulated sharpe ratio figures updated on an annual basis as more frequent data updates do not contribute materially to the analysis. 



performance. 

0.7 

FQ BRC 

Progression presents the additive Sharpe Ratio improvement

14 

Performance Statistics 


Annualized Risk (%) 

30 

25 

20 

15 

10 

5 

0 

21.1 

24.5 

Annualized Risk (%) Sharpe Ratio 

16.1 

14.4 

17.0 

10.4 

11.6 

11.8 

11.3 

S&P GSCI DJ UBSCI FQ BRC 

Simulation 

Overall High Volatility Regime Low Volatility Regime 

Sharpe Ratio 




0.9 

0.8 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0.0 

0.1 

0.3 

0.1 

0.0 0.0 

0.3 

0.7 

0.6 

S&P GSCI DJ UBSCI FQ BRC 

Simulation 

Overall High Volatility Regime Low Volatility Regime 

0.8

Drawdown (%) 

15 

Performance Statistics 


0 

-10 

-20 

-30 

-40 

-50 

-60 

-70 

1988 1990 1992 1995 1997 2000 2002 2004 2007 2009 2012 

S&P GSCI DJ UBSCI FQ BRC Simulation 

Correlation 




World Stocks are based off of the MSCI World Index (local Currency). World Bonds are based off of the Citigroup World Government Bond Index (local currency). 

0.40 

0.30 

0.20 

0.10 

0.00 

-0.10 

-0.20 

-0.30 

17% 

29% 

24% 

-16% 

-2% 

World Stocks World Bonds 

-19% 

S&P GSCI DJ UBSCI FQ BRC Simulation

16 

Bond Tail Risk Reduction 


Average Excess Monthly Return Over 30-Day T-Bills (%) 

10 

9 

8 

7 

6 

5 

4 

3 

2 

1 

0 

-1 

-2 

Expected Inflation 

-1.1 

0.8 

1.1 

-0.2 

1.1 

1.7 

0.2 

-0.6 

0.4 

0.7 

0.7 

0.8 

1.5 

-0.6 

-1.0 

1 2 3 4 5 Annualized 

Lowest 


Bond Return Quintiles 

Expected Deflation 

Highest 

Citigroup World Government Bond Index DJ UBSCI FQ BRC Simulation 

Balanced Risk Commodities simulation is supplemental information. Please see Balanced Risk Commodities – Simulated Performance (Gross of Fees) and Balanced Risk Commodities Strategies Composite Information 

and Balanced Risk Commodities Strategy (Gross of Fees) disclosures found at the end of this presentation for information concerning this simulation, the live composite, and the effect of fees on the performance. 

2.5 

1.5 

7.7

17 

Dollar Tail Risk Reduction 


Average Excess Monthly Return Over 30-Day T-Bills (%) 

10 

8 

6 

4 

2 

0 

-2 

-4 

-6 

-2.7 

1.3 

1.4 

-1.3 

0.5 

1.2 

-0.3 

0.0 

0.3 

0.6 

0.4 

0.8 

1.9 

-0.4 

-1.1 

1 2 3 4 5 Annualized 

Lowest 

Dollar Return Quintiles 

Highest 

Trade-Weighted Nominal Dollar Exchange Index: Major Currencies DJ UBSCI FQ BRC Simulation 

Sources: First Quadrant, LP, StyleAdvisor, Bloomberg LP, and Federal Reserve Board Dollar Index of major trading partners 



performance. 

-4.4 

1.5 

7.7

18 

Summary Performance Analytics 


Calendar Year Return 

1988 

1989 

1990 

1991 

1992 

1993 

1994 

1995 

1996 

1997 

1998 

1999 

2000 

2001 

2002 

2003 

2004 

2005 

2006 

2007 

2008 

2009 

2010 

2011 

-60% -40% -20% 0% 20% 40% 60% 

FQ BRC Simulation S&P GSCI DJ UBSCI 

Total Returns 

FQ BRC 

Simulation 


Quarter-to-Date 6.9% 11.5% 9.7% 

Year-to-Date 0.6% 3.5% 5.6% 

1-Year -2.1% 12.7% 6.0% 

3-Years (annualized) 12.6% 6.5% 5.3% 

5-Years (annualized) 10.0% -5.5% -3.0% 

10-Years (annualized) 17.4% 3.4% 5.2% 

Since Jan 1988 (annualized) 11.7% 6.5% 5.2% 

Statistics 

FQ BRC 

Simulation 


Risk (annualized) 11.6% 21.1% 14.4% 

Sharpe Ratio 0.7 0.1 0.1 




performance.

19 

Live Performance Overview 

September 2012 

Total Returns 

April 2011 – September 2012 

Balanced Risk 

Commodities Strategy – 

Live Performance 


Current Month 1.8% -1.4% 1.7% 

Quarter-to-Date 7.0% 11.5% 9.7% 

Year-to-Date 0.5% 3.5% 5.6% 

1-Year -2.2% 12.7% 6.0% 

Since Inception (annualized)¹ -7.5% -5.6% -8.4% 


¹Since Inception Date of April 2011. Please see Balanced Risk Commodities Strategies Composite Information and Balanced Risk Commodities Strategy (Gross of Fees) disclosures found at the end of this presentation 

for information concerning the live composite, and the effect of fees on the performance.

20 

Balanced Risk Commodities: Expected Benefits 

More Diversified Commodity Exposure 

Higher Expected Sharpe Ratio over the Long Term 

Targeted Risk Levels 

Similar Diversification Benefits with Stocks and Bonds

Excess Return Attribution vs. DJ UBSCI (%) 

22 

Attribution by Risk Dimension 

Simulation: January 1988 – December 2011 

40.0 

30.0 

20.0 

10.0 

0.0 

-10.0 

-20.0 

-30.0 

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Average 

Across Sectors Within Sectors Through Time 


Simulated attribution figures updated on an annual basis as more frequent data updates do not contribute materially to the analysis. 



performance.

23 

Simulation Disclosures 

Balanced Risk Commodities – Simulated Performance (Gross of Fees) Unless otherwise noted, performance figures do not reflect the deduction of investment advisory fees. These fees are described below. The 

returns shown will be reduced by the advisory fees and any other expenses the advisor may incur in the management of an investment advisory account. Simulated performance is no guarantee of the future 

results in a live portfolio using the strategy. Potential for profit is accompanied by possibility of loss. General Disclosures: Hypothetical or simulated performance results have certain inherent limitations. 

Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may under or over compensate for the impact, if any, of 

certain market factors, such as lack of liquidity or security positions that need to be rounded based upon contract size when live futures trades are executed. Simulated trading programs in general are also subject to 

the fact that they are designed with the benefit of hindsight. Further, backtesting allows the security selection methodology to be adjusted until past returns are maximized. No representation is being made that any 

account will or is likely to achieve profits or losses similar to those shown. Unless otherwise noted, performance returns for one year or longer are annualized. Performance returns for periods of less than one year are 

for the period reported. The simulated performance used in this presentation will differ from live performance experienced using the strategy for the following reasons: • The simulated performance was derived from the 

“backtesting” or the retroactive application of First Quadrant’s current proprietary model. • The simulation assumes that we adjust the risk and capital allocated to each sector or sub-sector on a monthly basis after the 

close on the last day of each month, whereas the live product may not adjust the allocations exactly at that time due to intra-month market movement and risk regime shifts. • The simulation assumes that the strategy 

guidelines are constant through the life of the portfolio, whereas, the guidelines for live portfolios may have changed over the life of each portfolio. • The simulation assumes fixed transaction costs whereas live portfolio 

transaction costs will be variable • The simulation assumes all trading takes place once a month (on the last day of the month) whereas live portfolios may trade often during the month.• Disclosures Specific to 

Simulation: This simulation was created in November of 2008 and updated every month end or quarter end. The simulation is constructed with the goal to diversify risk in a portfolio by strategically allocating risk to 

several commodities. Allocations are made to commodities within the following sectors: 1) Energy: WTI Oil, Brent Oil, Natural Gas, RBOB Gasoline, Heating Oil, 2) Agriculture: Wheat, Corn, Soybeans, Coffee, Sugar, 

Cocoa, 3) Industrial Metals: Copper, Aluminum, Lead, Zinc, Nickel, 4) Precious Metals: Gold, Silver and 5) Livestock: Live Cattle, Lean Hogs. The simulation balances risk across these so that each commodity has an 

equal risk footing in the portfolio. The simulation also attempts to balance risk relative to commodity weightings. The simulation targets overall portfolio risk allocations based on pre-determined indicators of market risk 

which may change over time. The simulation reflects an approximate 12% risk level. All income is reinvested monthly, no external cash flows are assumed. Investment Management Fees: Performance results 

presented are gross of investment management fees and trading costs. The FQ investment management asset-based fee schedule for this strategy, which is negotiable, is as follows: $0–$100 million, 0.50%; $100– 

$350 million, 0.30%; and more than $350 million, 0.15%. Asset-based fees are charged incrementally. For example, a $200 million dollar portfolio will be charged .50% for the first $100 million, 0.30% for the next $100 

million. Assuming a 0.40% advisory fee based upon a $200 million portfolio size with no increase in the asset value over a five year period, the compounded total return of a portfolio would be reduced by 0.40%, 

1.19% and 1.98% for the one-, three- and five-year periods, respectively. Incentive fee arrangements are available and negotiable.

24 

Balanced Risk Commodities Strategy 

Composite Information 

Composite Benchmark 

Balanced Risk Total 3-Year Standard 3-Year Standard 

Commodities Return Deviation Gross Deviation Number of 

Strategy Composite Gross (Annualized) (Annualized) Portfolios 4 

Total 

Composite Composite 

Dispersion Assets 

(%) 

3,4 

% of 

Firm 

(Millions USD) Assets 4 

Total Firm 

Assets 4 

Actively 

Managed 

AUM 

(Millions USD) 

1,4,5 

Total Firm Assets 

(Including Notional 

Values) 


1,4,6 


2011 (Apr-Dec) -11.4% – –

Edgar E. Peters 

Partner 

Co-Director of Global Macro 

Ed Peters is a First Quadrant partner coheading 

the firm’s Global Macro Strategies. 

He is involved in all aspects of product development: 

model building, risk measurement, 

risk allocation, and portfolio optimization. Prior 

to joining First Quadrant he spent 23 years 

with PanAgora Asset Management where he 

was, over time, an equity portfolio manager, 

Director of Tactical Asset Allocation, Chief 

Investment Officer of Macro Investments, 

and Chief Investment Officer. Prior to joining 

PanAgora, Ed was Investment Technology 

Manager at Interactive Data Corporation and 

an equity analyst/trader at Mutual Benefit Life. 

He has lectured extensively in the classroom 

as well as in conference settings. The author 

of numerous articles in investment journals, 

Ed is also the author of three books: Chaos 

and Order in the Capital Markets (Wiley, 1991, 

1996), Fractal Market Analysis (Wiley, 1994), 

and Patterns in the Dark (Wiley, 1999). Ed 

holds an MBA from Rutgers University. 

Susan A. Stannard 

Director 

Relationship Management 

Susan Stannard is First Quadrant’s director 

of client service with primary responsibility for 

keeping clients abreast of the firm’s research 

innovations, special projects, and performance 

across all firm products. In addition, she oversees 

the client service group that is accountable 

for client reporting, client consultation on tailoring 

portfolios and account management. Prior to 

joining First Quadrant, Susan spent nine years 

at Seneca Capital Management as a partner 

working with major client relationships. Before 

that she spent 16 years with Fluor Corporation 

working in various financial functions, ultimately 

overseeing the Investments group. She earned 

a BS in Business at California State University, 

Long Beach in 1981. 

BIOGRAPHIES

PLEASE RECYCLE 

800 East Colorado Boulevard, Suite 900 

Pasadena, California 91101 

phone 626.795.8220 fax 626.396.3298 

www.firstquadrant.com 

65 Walnut Street, Suite 580 

Wellesley Hills, Massachusetts 02481 

phone 781.283.5700 fax 781.283.5701 

This was printed on CLASSIC CREST ® paper from Neenah Paper, which is 

manufactured entirely Carbon Neutral, using 100% Certified Renewable Energy 

and made with fiber from well-managed forests.

To: 

From: 

Date: 

Subject: 

Commo odities Mana ager Review w 

Recomm mendation 

NEPC rec commends the t City of San S Jose Police 

and Firee 

Departmeent 

Retiremeent 

Plan (thee 

“Fund”) retain First Quadrant, LP L (“First Qu uadrant”) annd 

Credit Suuisse 

AG (“CCredit 

Suisse”) 

to provid de active inv vestment management 

for the Funnd’s 

7% targget 

allocatioon 

to 

commodities. 

In add dition, we re ecommend First F Quadraant 

and Credit 

Suisse mmanage 

the 3% 

target allocation 

to illiquid inflat tion-linked assets a on ann 

interim baasis. 

This reesults 

in Firsst 

Quadrant 

and Credit t Suisse being 

responsi ible for 10% % of the Funnd’s 

assets in 

aggregatee, 

which is consistent with w the Fun nd’s exposure 

since thee 

two managgers 

were ooriginally 

retained. 

Backgro ound 

City of San Jose Police 

and Fire 

Departmeent 

Retiremment 

Plan 

Dan Le eBeau and Allan A Martin 

Decem mber 10, 201 12 

In Octob ber 2009, the 

Fund approved 

a long g-term strattegic 

asset allocation thhat 

includedd 

a 

10% targ get allocatio on (~$250 million m at the 

time) to ccommoditiess. 

When thee 

Fund originnally 

invested in commod dities in December 

2009 9, Russell Immplementattion 

Servicess 

(“Russell” ) 

was retained 

to pass sively mana age the expo osure using Dow Jones/ /UBS Commmodities 

Index 

swap agreements 

with w three dif fferent coun nterparties. This was coonsidered 

sttep 

one in thhe 

process, and this inv vestment was 

intended d to provide immediate exposure too 

commoditties 

during th he asset allo ocation transition 

that occurred o in December 22009, 

givingg 

the plan 

immediate 

diversific cation at the e plan level while activee 

managemeent 

was souught. 

At the Au ugust 19, 20 010 investm ment committee 

meetinng, 

the Fundd 

approved a $250 milliion 

investme ent in two actively 

man naged comm modities inveestment 

straategies 

thatt 

are managged 

using a risk r parity approach 

by First Quadr rant and Creedit 

Suisse ( ($125 millioon 

each). Thhis 

was view wed as step two in build ding out the commoditiees 

allocationn. 

Step threee 

of the 

process, which was not complet ted, was int tended to foocus 

on adding 

additionnal 

sources oof 

alpha, in ncluding long g/short strategies. 

Step 1 – Gain Passiv ve Exposure e 

A. Goal: G This in nvestment was w intende ed to provide 

immediatte 

exposure to commoddities 

during 

the as sset allocation 

transition 

that occurrred 

in Deceember 

20099. 

B. Im mplementat tion: Used 

co ommodities. 

synthetic 

instrumennts 

to gaain 

passivee 

exposuree 

to 

900 Vetera ans Boulevard d | Ste. 340 | Redwood R City, , CA 94063-17741 

| TEL: 6500.364.7000 

| wwww.nepc.comm 

CAMBRIDGE 

| ATLANT T A | CHARLOTTE 

| CHICA A GO | DETROO 

IT | LAS VEGG 

AS | SAN FRANCISCO

a. Russe ell was pas ssively man naged the exposure to 

commodities 

using Dow 

Jones s/UBS Com mmodities Index I swap 

agreemeents 

with three diffeerent 

count terparties: UBS U ($80 M) ); Merrill Lyynch 

($80 M); 

Goldman Sachs ($977 

M). 

C. Pros: 

a. Provid ded immedia ate diversification 

beneefit 

to the pllan; 

enhancced 

risk-adjuusted 

return n potential at a the Fund level. 

b. Provid ded directio onal market t capture off 

commoditty 

beta, and 

thereby ssome 

CPI protection. 

c. Very reasonable investor te erms: high liquidity, hiigh 

transparency, 

relattively 

inexpensive 

fees. . 

D. Cons: C 

a. Index x volatility is 

relatively high and ttends 

to bee 

dominatedd 

by the ennergy 

sector r. 

b. No op pportunity to o capture alpha. 

E. Recommenda 

R 

ation: Trans sition from passive p to aactive 

expossure. 

a. Enables 

strategic c exposure to t commoditties 

beta annd 

alpha. 

b. Beta can c be activ vely manage ed to lower volatility. 

c. Increa ases potential 

capture of o alpha in aan 

inefficiennt 

market. 

d. Emph hasize highly y liquid exp posure; enaables 

quick transition if 

necessaryy 

and 

provid des direction nal market capture. c 

Step 2 – Transition to Active Ma anagement 

A. Goal: G Seek actively a man naged comm modities straategies 

to prrovide 

less vvolatile 

betaa 

and 

to o increase alpha a potent tial within th he allocationn. 

a. Rema ain focused on portfolio-level 

benefits 

(e.g. divversificationn 

of risk thrrough 

lower correlation of commod dity return sstreams 

to sstocks 

& bonnds). 

B. Im mplementat tion: Conduct 

search for activve 

manageement 

to replace passive 

ex xposure. 

a. Lower r volatility in 

the beta. . Focus on beta preserrvation 

withh 

lower volaatility 

than the t index. 

b. Achiev ve an alloc cation that derives equual 

risk froom 

the commmodity 

secctors, 

creating 

a more diversified d commodities 

c 

s investmennt. 

c. Some e alpha potential; 

prima arily “enhancced 

index” sstrategies. 

C. Pros: 

a. Contin nues to provide 

diver rsification bbenefits 

to the Fund; enhances risk- 

adjusted 

return potential. p 

b. Contin nue to pro ovide direct tional markket 

capture of commoodity 

beta, and 

thereb by some CP PI protection n. 

c. Lower rs volatility. 

d. Increa ases opportunity 

to cap pture alpha. 

e. Fairly reasonable e investor te erms: high liiquidity, 

higgh 

transpareency. 

2

D. Cons: C 

a. Introd duces active e manager risk. r 

b. Increa ases costs. 

c. While achieving lower volat tility in the beta may certainly bbe 

feasible, pure 

“risk parity” p in th he commodit ties beta peer 

se, may bbe 

difficult too 

achieve. 

E. Recommenda 

R 

ation 

a. Invest 

approxima ately $125 Million eacch, 

or 50% of the $2550 

million taarget 

alloca ation, in Firs st Quadrant and Credit Suisse. 

Step 3 – Add Addit tional Active e Manageme ent (potentiial 

future coonsideration) 

A. Goal: G Continue 

along the e path of ac ctive commoodities 

manaagement. 

a. Maintain 

portfolio o diversificat tion benefits. 

b. Rema ain focused primarily p on n capturing ccommodity 

market beta. 

c. Increa ase alpha po otential by diversifying 

d 

return drivers. 

d. Better 

position th he commodi ity programm 

to weatherr 

a variety oof 

capital market 

enviro onments and 

economic regimes (i. e. rising & ffalling 

inflattion). 

B. Im mplementat tion: Increas se long-only y active riskk; 

add long- short strateegies 

a. Great ter active ris sk through long-only l coommodity 

sstrategies 

with 

more divverse 

return n drivers (i.e e. beyond ro oll yield management). 

. 

b. Introd duce long-short 

commo odity strategies; 

beneffits 

of relativve-value 

traading 

partic cularly evide ent in down markets annd 

non-direcctional 

(sideeways) 

markkets. 

C. Pros: 

a. Divers sifies driver rs of potenti ial return inn 

the commoodities 

alloccation 

(top-ddown 

global 

macro bets; 

intra-com mmodity trades). 

b. Lower r net expo osure can reduce r marrket 

directiionality 

to protect aggainst 

downs side market t environme ents & can reeduce 

volatility. 

D. Cons: C 

a. Increa ases active manager ris sk. 

b. Introd duces explic cit leverage to the alreaady 

implicit leverage of buying futuures. 

c. Highe er costs. 

d. Lower r liquidity. 

E. Recommenda 

R 

ation: Add additional a ac ctive exposuure. 

a. Revisit 

potential allocation of 

Step 3 witthin 

the nexxt 

12-18 moonths. 

Investm ment Thesis s 

There ar re two main portfolio lev vel benefits to long-terrm 

investingg 

in commoddities: 

enhanced 

risk-adjus sted returns s and improv ved inflationn 

protection. 

Both potential 

benefitts 

may be attributable 

a 

in large part 

to the low w correlationn 

of commoodities 

to thee 

more 

traditional 

investme ents (e.g. sto ocks and bo onds) which tend to domminate 

institutional 

investme ent portfolio os. 

3

Diversific cation 

Commod dities can be enefit an inv vestment pr rogram by diversifying 

tthe 

portfolioo, 

thanks to the 

low corre elation of co ommodities to most oth her financial instrumentts. 

The counnter-cyclical 

nature of 

commodities 

can help p the overall l portfolio acchieve 

betteer 

risk-adjusted 

returnss 

over full market cyc cles. Commo odities can rise r in valuee 

when equitties 

and fixeed 

income 

instrume ents fall. Thi is is because e the under rlying returnn 

drivers forr 

commoditiees 

are distinnct 

from the e market for rces that drive 

most sto ock and bond 

prices. Thhe 

consequeent 

low 

correlatio on of comm modities to th hese traditio onal assets can enhancce 

portfolio ddiversificatioon 

and redu uce overall risk. r 

The low correlation of returns among a comm modities proovides 

an addditional 

divversification 

benefit. A well-diver rsified comm modities pro ogram has eexposure 

to a variety off 

global retuurn 

drivers, taking t adva antage of this 

low correlation 

and mmitigating 

thhe 

portfolio risk of any one 

asset cla ass or marke et sector experiencing 

a short-termm 

correctionn. 

Inflation Protection 

Rising longer 

term inflation 

is among 

the greatest g riskks 

that invesstment 

portfolios 

may fface, 

yet we have h found that t many plans p are under-exposedd 

to inflation-hedging 

sstrategies 

suuch 

as comm modities. Com mmodities can c play an important rrole 

in instittutional 

cliennt 

portfolioss 

by 

helping to t preserve their purcha asing power r as inflationn 

rises, provviding 

a “reaal” 

or inflation 

adjusted d return. Hei ightened att tention to meeting m liabiilities 

and a rapid expansion 

in thee 

magnitud de and scop pe of exogen nous events s—among thhem 

rising innflation—higghlight 

the 

strategic c advantages 

of commo odities to inv vestment poortfolios. 

Many ins stitutions fac ce annual lia ability requi irements annd 

employ liability-senssitive 

investmment 

strategie es to help meet m them. One O of the biggest b threaats 

to meetting 

a liabilitty 

can be thhe 

loss of purchasing 

power p due to o inflation. Institutions 

I 

face particuular 

challengges 

with reggard 

to inflatio on, as their principal lia ability can be b very inflation-sensitivve. 

Rising innflation 

can 

significan ntly erode the 

value of an institutio on’s financiaal 

assets. Gaains 

in inflation 

can meean 

losses in a traditiona al investment 

portfolio, , as they can 

decrease the value of 

dollars speent 

and may y require liqu uidation of assets a to co ontinue fundding 

liabilitiees. 

Investm ment Struct ture 

The Plan’s 

original allocation a to commoditie es was passsive 

exposurre 

using Doww 

Jones/UBBS 

Commod dities Index swap agree ements. Due e to the inheerent 

transpparency 

andd 

inefficienciies 

of 

the vario ous commod dity indices, we believe active mannagement 

caan 

add valuee 

in the 

commodities 

space. There are several s strategies 

that seek to cappture 

these iinefficiencies. 

Risk Pari ity 

Risk Pari ity is a strat tegy in whic ch investors allocate dollars 

across various asssets 

based oon 

the expe ected volatility 

of assets s rather than 

their return. 

Commoddities 

managers 

utilizinng 

this investment 

stra ategy target an equal risk 

contributtion 

from eaach 

commoddity 

sector 

(livestock, 

industrial 

metals, precious 

meta als, energy, and agricullture). 

Curreent 

passive 

commodity 

indices, such as the e S&P GSCI, have skewwed 

contributions 

to riskk. 

The S&P GGSCI 

has appr roximately 70% 7 of its weight w in the e energy secctor, 

which in turn commprises 

approxim mately 95% of the risk while the re emaining fouur 

sectors aaccount 

for jjust 

5% of tthe 

total risk k. Similar funds 

are utilizing 

risk pa arity strateggies 

at the total 

portfolio 

level as eequity 

contribut tes a signific cant portion n to the overall 

risk of a total fund. . Similar to the S&P GSSCI, 

a 

4

Fund who 

allocates 60% of its assets a to eq quities receivves 

approximately 

90% % of its risk 

contribut tion from eq quities. Even n the DJ UB BS Commodiities 

Index, which was the Fund’s 

benchma ark for its co ommodities investment ts, derives 449% 

of its risk 

from thee 

energy secctor, 

despite the t fact that t it caps the e weight of the t energy ssector 

at 333%. 

The volatility 

of the energy sect tor contributes 

to the hhigh 

percenttage 

of enerrgy 

sector riisk 

within th he major com mmodities indices, 

and as a result, , the major commoditiees 

indices 

returns are a largely dependent d 

on o the move ement of thee 

energy maarkets, 

while 

other low risk, 

non-cyclical 

commodities 

provid de little dive ersification bbenefits. 

Thhe 

risk parityy 

approach 

targets better b risk-a adjusted returns 

with th he commodiities 

allocatiion 

while maaintaining 

diversific cation benef fits within th he broader portfolio p conntext. 

Credit Suisse S 

The Cred dit Suisse To otal Commo odity Return Strategy offfers 

an enhhanced 

indeex 

approach to 

managin ng commodit ties. The str rategy is designed 

to ouutperform 

tthe 

custom iindex 

by 

actively managing the 

return on n the roll yie eld, while reemaining 

neeutral 

to thee 

spot returnn 


the chosen 

benchma ark and man naging colla ateral conservatively. 

QQuantitative 

and qualitative 

research is employe ed to identify y optimal pe eriods to rolll 

the underrlying 

contraacts. 

The gooal 

is 

to achiev ve a higher return relat tive to the ro oll yield gennerated 

withhin 

the indexx. 

The passive 

spot inde ex exposure e and the ac ctive roll ma anagement aare 

achievedd 

through thhe 

use of 

commodity 

futures. 

Potential l Advantage es 

� Highly H liquid contracts (a at most 6 months) m 

� Solid 

beta; on o average go 2-4 mo onths out oon 

the futurres 

curve; ttheir 

strenggth 

is 

beta 

preservation 

� Size: 

$5.5B in the flagship 

produc ct; primarilyy 

institutionnal 

investorrs; 

roughly 50% 

are 

Pension plans p 

� Lo ong, GIPS-c compliant tr rack record (1996 incepption 

date) 

� Team 

is stab ble and continues 

to gro ow at a meaasured 

pace 

� Cash C collater ral is conser rvatively ma anaged; nott 

an alpha soource 

� Lo ow transact tion costs + timing of tr rades helps mitigate voolatility; 

very 

active trading 

� Nimble N roll timing 

of con ntracts; enables 

beta annd 

alpha 

� Risk R budget mindset—fo or beta and d alpha possitions; 

e.g. size bets aaccording 

too 


sp pread oppor rtunity & vo olatility of th hat spread; risk group hhas 

indepenndent 

authorrity 

� Quantitative 

Q 

process 

opportunities 

s 

� No N ISDA agre eements ne ecessary 

to manage e risk; usse 

fundamentals 

to 

5 

identify reeturn

Potential l Disadvanta ages 

� Modest M alpha; 

comes primarily p fro om the “rooll 

spread ooverlay”; 

doo 

not use oother 

potential 

com mmodity alp pha drivers (e.g. ( relativee 

value traddes; 

global mmacro 

posittions; 

non-benchmark 

trades) 

� Risk R parity in 

the beta is available e in back-teest 

form only; 

may be able to proovide 

lo ower volatile 

beta, and d beta pres servation iss 

a demonsstrated 

capability 

at CCredit 

Suisse, 

but risk r parity in n the beta (a as requestedd 

by the clieent) 

is a neww 

strategy 

� Risk R manage ement system 

did not seem s sufficieently 

robustt/customized 

to addresss 


unique 

needs s of the com mmodities market m 

� No N other ava ailable options 

for cash collateral—ee.g. 

TIPS beeta 

First Qu uadrant 

The First t Quadrant Balanced B Risk 

Commod dities Strategy 

(BRC) offfers 

an enhhanced 

indexx 

approach h to managing 

commod dities. The strategy s is ddesigned 

to outperform the index bby 

utilizing First Quadra ant’s proprie etary, rules-based 

Markket 

Risk Inddex 

(a combbination 

of the 

CBOE Vo olatility Inde ex (VIX), cre edit spreads s, global moonetary 

policcy 

and globaal 

growth), 

which attempts 

to derive 

equal risk contrib bution from each of thee 

commodityy 

sectors. 

Quantitative 

researc ch is employ yed to ident tify rebalanccing 

needs. The goal is to provide 

diversific cation across 

and within n commodity 

sectors ass 

well as acrross 

time. 

Potential l Advantage es 

� Highly H liquid contracts 

� Strong 

beta preservation n with less volatility v 

� Size: 

Low AUM; A produ uct is a car rve out of an existingg 

strategy with the ffirm’s 

Essential 

Bet ta strategy. . Gives the Fund somee 

leverage when discuussing 

guideelines 

fo or the customized 

strategy 

and dis scussing soluutions 

to pootential 

issuees. 

� Deep, D stable team with considerable e credentialls 

from acaddemia 

� Cash C collater ral is conser rvatively ma anaged; nott 

an alpha soource 

� Trading 

is a critical component, 

with w significcant 

resourcces 

dedicatted 

to analyyzing 

tr rade strateg gies and the subsequent 

results 

� Quantitative 

Q 

process to manage risk k 

� No N ISDA agre eements ne ecessary 

6

Potential l Disadvanta ages 

� Modest M alpha a; comes primarily 

from 

diversificcation 

acrosss 

commodiities 

sectorss 

and 

dynamic 

reb balancing; do d not use other potential 

commmodity 

alphha 

drivers (e.g. 

re elative value e trades; glo obal macro positions; nnon-benchmmark 

trades) ) 

� Risk R parity in 

the beta is available e in back-teest 

form only; 

may be able to proovide 

lo ower volatile e beta, but risk parity in the betaa 

(as requessted 

by the client) is a new 

st trategy 

� No N other ava ailable options 

for cash collateral—ee.g. 

TIPS beeta 

� Size: 

Low number n of investors in n the strateegy 

yet; product 

is a carve out oof 

an 

ex xisting strat tegy with th he firm’s Ess sential Beta strategy 

Conclus sion 

We are comfortable 

c 

with the cu urrent alloca ation to commmodities 

annd 

we feel thhe 

Fund maay 

want con nsider addin ng an additio onal source of alpha (coompletion 

oof 

step 3) wiithin 


allocation 

before ma aking any ch hanges to th he current sstructure. 

WWhile 

performmance 

for thhese 

strategie es has struggled 

year-to o-date in 20 012, both haave 

outperfoormed 

the DDJ/UBS 

Commod dities Index since their inception in April 2011 (Credit Suisse 

- -6.9% % vs. -10.2% %; 

First Qua adrant - -9.3 3% vs. -10. .2%). The Fund F may also 

want to cconsider 

thee 

benchmarrk 

against which w First Quadrant Q is measured going g forwaard, 

as meassuring 

the pperformancee 


their stra ategy against 

the Credit 

Suisse Custom 

Commmodities 

Bennchmark 

doees 

not proviide 

an accur rate represe entation of the 

portfolio’s 

intended performancce. 

7

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