Meaningful out-sample test? How does Walf Forward Analysis really work?

Discussion in 'Strategy Development' started by mizhael, Mar 24, 2010.

  1. I used rolling-window in-sample training and out-sample testing,

    and then concatenate the out-of-sample testing returns all together,

    forming a return series,

    and calculate Sharpe ratio on that overall-out-of-sample concatenated return series,

    however the result is very sensitive to the windows sizes of in-sample periods and out-sample testing periods.

    Let's say if I pick in-sample window size to be 500 data points and out-sample window size to be 250 data points, vs. in-sample window size 250 and out-sample window size 250, the Sharpe ratios are very different.

    Any pointers about walk forward analysis?

    Any popular choice of window size that makes sense?

    Shall I reduce out-sample-window size to be 1 so that strategy recalibrates every day?

    Any thoughts?

    Thanks a lot!