FX MANAGERS
life or back-test. Changes in monetary
policy regimes and
policy reaction functions dramatically alter currencies’ sensitivity to economic variables. Assumptions no longer hold, and correlations breakdown. Over the past three years, many central banks have been aggressive like never before in managing ranges, trends and volatilities in their own currencies. For example, exchange rates in Brazil, Chile and Colombia used to hold very stable correlations
to
external factors such as commodity prices. That has no longer been the case over the past 2-3 years. In developed markets we can look at the extreme experience of the Swiss National Bank, who has set and defended a
floor on the Euro/
Swiss exchange rate at all costs since September 2011.
Another example can be found in global interest rate markets having all converged towards the zero bound, creating an environment of suppressed volatility in yields, which are a major driver of currencies. The
scale of this phenomenon is simply unprecedented, and the information content in relative interest rate differentials for currency trading has in many cases disappeared.
FXTM Do
you use any form of optimization? If so, how do you
FX
understanding of the fundamental regimes behind those data. For example, looking at historical data for emerging market currencies and macro variables requires a deep understanding of changing monetary policy regimes, mandates and reaction functions. These create what we call “correlation breakdowns” in the historical patterns. Optimization techniques tend to overlook these
idiosyncrasies,
frequently leading to erroneous conclusions.
In the past, I investigated several optimization techniques aimed at combining different systematic investment strategies into an overall portfolio. I worked with such as mean-variance
make sure it doesn’t create curve fitting and confirms robustness of the model?
AL No, we don’t. In my opinion, any optimization technique is a data mining exercise by definition. This makes me very skeptical. I think rigorous and extensive analysis of data is an indispensable building block of any investment strateg y; but it is equally important to have
an ongoing qualitative
optimization, minimum variance, equal risk contributions, etc. Even for a liquid asset class like FX, properly factoring in transaction costs and slippage risk erodes large parts of any performance improvement achieved over a naïve equally weighted allocation across strategies. Overall, I find that on an out-of-sample basis, net of transaction costs, a naïve equally weighted allocation represents a challenging benchmark to beat.
FX TRADER MAGAZINE July - September 2013 59
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