FX FX MANAGERS
the universe of acceptable markets would certainly be larger because a bad fill would not ruin the profitability of a trade. Tat said, as one begins to trade less mature currency pairs, gap risks and fast markets become much more likely.
JW: When developing strategies,
how do you allocate your time between building entry signals, exit signals and money management rules? MM: We have found that every
strategy generates alpha in three ways: entry criteria, exit criteria, and money management. We tend to devote equal attention to each of the three components because each one is essential. However, each system will have its own unique traits and composition. Certain trading systems will emphasize the entry signals and use more generic exit strategies, others will emphasize the latter. Te important consideration is that it is essential that the strategy be robust and that the model does what it is supposed to do.
JW: How much time do you allocate
to research and development of existing or new strategies? MM: We continuously attempt to
expand the number of systems and markets without changing the core risk parameters and return profile of the program. In January 2002, we expanded short-term trend-following and short-term trading strategies, while eliminating our long-term trend- following strategies. We believe that long-term trend-following returns are commoditized and there is no alpha to be derived in that space. Consequently, we can achieve a higher Sharpe ratio by being more short-term oriented. In March 2005, we integrated two
50 FX TRADER MAGAZINE July - September 2010
of our major research studies into the design of Conquest Macro FX. Tese studies covered the relationship between short-term strategy returns and market risk appetite. Conducted in parallel, the studies produced two significant conclusions: 1. Te general risk appetite level
of the market environment can be measured and that it tends to change slowly over time. 2.
Short-term trend-following
strategy returns provide conditional long-volatility exposure (i.e. they exhibit high correlations to the change in volatility when volatility rises significantly but are only slightly correlated to the change in volatility when volatility rises slightly or declines). Using the proprietary metric we
devised to measure market risk aversion, our Conquest Risk Index, we observed that market risk appetite was quite high at the time. Tis period of risk accumulation created an environment that would likely continue to be unfavorable for Conquest Macro FX’s long-volatility strategy. Te latter conclusion leſt us confident that we could preserve our long-volatility profile should there be a rise in volatility while reducing the drag on Conquest Macro FX’s returns. Harnessing these two effects led us to adjust Conquest Macro to become a dynamic strategy allocating risk based on the risk environment among our sub-strategies. In 2010, we improved the strategy
further by integrating our environmental analysis with observations regarding downside exposure. Tis refinement is an extension of the research that led to the 2005 strategy enhancement. Whereas the prior enhancement
focused on the composition of the portfolio but kept leverage more or less constant, this enhancement adjusts both the leverage and system composition of the portfolio.
JW: Do you believe in ever-valid
rules, or every strategy loses its accuracy sooner or later? Have you ever found strategies that come back into phase aſter a long time in negative? MM: I think the performance of
trend-followers over the past 30 years suggests that trend-following has been a fairly robust, if unspectacular strategy, even with its drawdowns. Within our strategy, we have models that been trading since 2001 or earlier and are still profitable. Models tend to fail for a number of reasons, but here are five of the most common: 1. Tey are over-optimized 2. Tey require more liquidity
than is reasonably available in the market 3. Tey attempt to exploit market
behaviors that no longer exist 4. Tey attempt to exploit market
behaviors that occur infrequently 5. Tey have significant tail risks Models that come back into phase
typically either work infrequently or exhibit sufficiently large tail risks that they are removed from trading. Te risk is that it is difficult to infer whether a model will continue to generate gains aſter a profitable run unless it is possible to identify the factors that contribute to its success and determine whether those factors are present at any given time.
JW:Do you adjust systems parameters
to cope with new market conditions? MM: No, our system parameters are not changed to meet market conditions.
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