WHAT FINK MIGHT DO WITH BGI - FTSE

RISK MANAGEMENT IN HIGH-FREQUENCY TRADING
30
In the Markets
One sector of the market that really
needs to wake up to the issue of realtime
risk management is the hedge fund
community. The Obama administration
has already begun to take steps by
reforming the regulatory environment in
the United States. The government in
the United Kingdom has announced,
meantime, its intent to effect sweeping
reforms of the Financial Services
Authority. While it might not be crystal
clear how these reforms are going to
affect hedge funds, what is clear is that
(like it or not) hedge funds will be next in
the line of fire for regulators.
There is a groundswell of opinion
that an essential task for the regulation
of hedge funds is to source and
aggregate data on leverage and
positions. For the regulation of hedge
funds to stand a chance of being
successful, regulators will need to be
able to track the concentration of hedge
funds by assets and by strategies, and to
understand how the failure of one firm
might affect others. Real-time risk
management through the pre-trade
checking therefore is critical.
Even so, there are a number of issues
to consider for hedge funds and
institutions. Pre-trade risk management
is perceived to add latency to the
process. Moreover, the issue of how a
broker’s handling of buyside order flow
impacts anonymity also has to be
tackled. Having visibility into the fund’s
trading patterns could potentially
provide the broker the ability to frontrun
the orders and reverse-engineer the
algorithms, among other things. So how
do you solve the latency and anonymity
problems and still control the risk?
Some look to broker neutral real-time
systems, while others employ the trick
of abstracting the positions/exposure in
real-time from the details of the order
flow that pushed the exposure to that
level in the first place. Either way, it is
important to note that minimising the
latency impact of pre-trade risk
checking is not only essential, but also
achievable through event driven, realtime
approaches, as compared to the
other traditional methods of checking
trades before being placed.
In addition, real-time risk
management does not have to impact
anonymity if handled well. It’s generally
accepted that the buyside’s way around
this issue is via the DMA route.The best
systems for doing this are those that have
no knowledge of the trading algorithm
and do not deduce the algorithm from
seeing the order flow; they only care
about issues such as instantaneous perorder
risks or total position/exposure
over time, regardless of how it got there.
Impact of algorithms
The advantages of real-time risk
management are crystal clear. It allows
traders to benefit from more aggressive
limits, which safely increases trading
volumes and thereby increases
profitably from high-frequency trading
strategies. It preserves the
buyside/sellside relationship when used
in conjunction with DMA or any other
instance where the broker must
otherwise either overly constrain or
blindly trust the trading activities of its
client.Another plus point for the buyside
is that direct adoption empowers it to be
more broker-neutral and, as many will
find out, hold off the regulators if
implemented widely enough.
Within all this talk of real-time risk
management and high-frequency
trading, it is critical not to forget the role
and impact of algorithms. While the
earthquake that shook the markets last
year undoubtedly drove computerorientated
investors temporarily back to
more traditional methods and trading
styles, many brokers expect the growth
curve in electronic trading to continue.
To this end, there is still a strong appetite
for algorithms which aggressively
complete transactions with as little
latency and as unobtrusively as possible.
According to Sang Lee, a managing
partner at Aite Group, the first
iteration of aggressive algorithms
were more about looking for liquidity
in the displayed market, but now
algorithms have evolved to the point
where aggressive algorithms seeking
liquidity can operate simultaneously
in both dark and displayed venues,
allowing for greater efficiency and
speed of execution. Aite Group
research has also highlighted the fact
that leading algorithms in the
“aggressive-algo” category have
grown significantly in the past year.
Those trading in foreign exchange
can testify to this trend. Despite the
downturn in equities, many brokers
trading FX benefited as long as the
algorithms they used could
accommodate attendant larger spreads
and higher volatility. Some had to
customise their algorithms to do so; but
once done, the new algorithms worked
well and to quote a trader were“making
money hand over fist”.There have been
cases of buyside firms trading primarily
in equities prior to the market
meltdown at the end of 2008 that then
wanted to start trading foreign
exchange with algorithms as quickly as
possible because of the opportunities to
capture gains on new volatility, which
was not expected to last very long.
Ultimately all this points to a shift in
the landscape bought about by
volatility, regulation and competition.
Traders and investors are constantly
looking at ways to forge ahead of
competitors while trying to not to fall
foul of the regulator and an industry
stung by events of the last year. Traders
eventually and often reluctantly adhere
to the old saying in racing: “Never drive
faster than your guardian angel can fly.”
Adopting real-time risk management is
a step in the right direction, helping the
guardian angel fly at the speed the
traders need to drive in order to win
their race in high-frequency trading.
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