I've been back-testing a trading system that balances a portfolio between the S&P (via SPY) and 20-year Treasury bonds (via TLT). Through data mining, I've been able to identify a trading strategy that produces a Sharpe ratio of 2.06 over a 6-year back-test.
I'm now trying to test my strategy against bootstrapped data as I'm concerned about the data mining bias that likely exists. To start, I'm calculating the daily % change of each ETF and re-sampling to reconstruct new prices to run my strategy against.
My question is should I re-sample each ETF independently of the other? Meaning, do I re-sample the distribution of SPY and then re-sample the distribution of TLT ignoring how each moved in relation to the other on a given day? Or should I force the re-sample to maintain the correlation by following the re-sampled order for each bootstrap test?
I hope this makes sense!