dusktrader,

A couple of other places to look:

1) overfitting to past data - some of the great work you did on using binary logic to optimise days / times etc. could lead to overfitting. Do you still have the divergence on simpler minimally optimized algos.
Relatedly - there recently was a thread on degrees of freedom which describes this phenomenon better. However, beware elimination of degrees of freedom by testing and rejecting many optimizable parameters for a single value - that process introduces all new data mining biases.


2) how long are you testing vs how long did the test period run?
Not sure what an algo would have to be trained and tested on to be fit for the last week and a half of market action! Come to think of it Dec wasn't great either :-)

I'm very proud I restricted my discretionary trading drawdown% to double digits only this past week ;-)