weiguang-zz
commented
4 years ago The paper describes a blocked bootstrap method with studentized test statistics. It can deal with long-tail distribution and time series characteristics of the return very well. I studied for a long time, Hoping to implement it with python
How can I build my confidence that my strategy returns better？
for example, I have to return sequence. R1 is from my strategy, R2 is from benchmark R1: [r_11, r_12, r_13, r_14 .... r_1n] R2:[r_21, r_22,r_23, r_24 ... r_2n]
I have read a good paper:Robust performance hypothesis testing with the Sharpe ratio, The paper describes a method to test the sharpe ratio difference between two return series. In my opinion this method makes sense. So I want to implement this. before this, I hope to get your opinions about this: 1 Did you encounter this problem？ 2 Are there other better ways to evaluate a strategy？ 3 Any other your thoughts？
Looking forward to your reply！ thank you