I posted this on Cross Validated a month ago, but I didn't get any answers. Sorry for the second post!
I'm wondering about the whole process of testing/data-mining for a strategy and THEN testing on bootstrapped data. Does it make sense to bootstrap your data first and then data-mine for the best result?
This came to me because my current strategy had significant decay when I tested it against the bootstrapped data. The initial strategy is one that re-balances between the SPY and the TLT on a monthly basis. Back-tested on 6 years worth of data (or 72 total trades), the strategy has a Sharpe of 2.06. But when I test it against the bootstrapped data, the Sharpe ratio drops significantly to 1.04.
It seems like I'm ultimately looking to raise the 1.04 number, and to do that I'll need to
start the data-mining process over again to find a new back-tested strategy
test again against the bootstrapped data.
So can I skip step #1? Obviously this will require some significant computational power.