Way of the turtle

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Way of the Turtle

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Monte Carlo simulation using scrambling of trades tends to
dilute those very real occurrences because it spreads the trades
apart so that they no longer have adverse price movement on the
same days.
Many software packages that implement Monte Carlo simula-
tion offer a way to generate new curves by using equity curve scram-
bling. However, they do not take into account another important
issue. I also have found through testing and experience that the
periods of bad days at the end of large trends and the magnitude of
those bad days are much worse than one would expect from ran-
dom events. At those times of major drawdown, the equity curve
for a trend-following system exhibits serial correlation or correla-
tion of one day’s net change with the preceding day’s net changes.
Put more simply, the bad days tend to cluster in a way that one
would not expect to occur randomly.
Using the same recent example of the drawdown in gold, silver,
and sugar in spring 2006, if one scrambled only daily net changes,
the long streak of high-magnitude changes in equity from mid-May
to mid-June would be lost as it would be very unlikely that those
changes would come together if you randomly drew from a distri-
bution or even from the actual equity curve.
To account for this in our simulation software, at Trading Blox
we use equity curve net changes but allow for scrambling by using
multiday chunks of the curve rather than just a single day’s change.
That way the simulated equity curve preserves the grouping of bad
days that one encounters in actual trading. In my testing, I use 20-
day chunks for equity curve scrambling and find that this preserves
the autocorrelation of the equity curve and gives the resulting sim-
ulation better real-world predictive value.
On Solid Ground
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