I am thinking of adding another strategy performance metric to
optimizer, to complement Net Profit, Max DD, Profit Factor, Kelly, and
PI. The new metric name would be "robustness", or its opposite,
"sensitivity". There is already a way to determine how sensitive the
strategy performance is with respect to changes in parameters, which
is the optimization maps, but when the number of parameters exceeds 2,
it becomes somewhat difficult to visualize it. The "robustness" metric
would be a single number which would measure the volatility of
performance results when the optimal strategy parameters change by a
certain small amount, say 10%.

For example, consider these two strategies:
Strategy A has 3 parameters, 10-100-50. Its best factor is 3.0. When
its parameters change by 10% (such as 9-90-45), profit factor becomes
as low as 1.0
Strategy B has 3 parameters, 200-10-10. Its profit factor is 3.0. When
its parameters change by 10% (such as 180-9-11), profit factor becomes
as low as 2.5

Clearly, strategy B is superior to strategy A because it is much less
sensitive to small changes in parameters. To put it in another way,
strategy B is more robust than strategy A.

To calculate the "robustness" metric, we need a piece of code to
iterate through the brute force optimization results, and to compute
some sort of performance volatility measure. It could be standard
deviation of performance near a given set of parameters, or it could
simply be the "worst" performance near a given set of parameters. Once
calculated, the robustness metric would be shown as a column in the
optimization results table.

At the moment, I am working on various other enhancements to JBT, so I
am looking for someone else to implement the robustness/sensitivity
metric. If you would like to code it, please respond in this thread.





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