Probabilistic Analysis of Trading Systems, Paper
Edit: I forgot to add the part on permutation subroutines.
Topics Discussed:
Preview, with Code given for Section 10.1
The remainder of the paper discusses more powerful techniques in permutation testing. Suppose we have a momentum strategy of moving average pairs, and our Sharpe was 1.10. We are interested in asking questions like;
i) what is the probability of getting Sharpe 1.10 or better if we went long as often but at random timings as opposed to our rule based timing? (asset picking)
ii) what is the probability of getting Sharpe 1.10 or better if we went long some other asset B when our rule said to buy A? After all, markets are correlated. If we are good at timing (smart-beta), what is our alpha component of the total return?
iii) what is our overall skill at picking and timing in relation to market drift? (trader skill)
iv) Given 10 another moving average pairs, which of the moving average pairs have statistically significant edge?
For Section 10.2, the code integrated with the Russian Doll Framework is scheduled for release on: Week 1, 23’.
Techniques such as the bootstrap analysis are to be released once we have covered the theoretical ground on statistical bootstraps. Next post scheduled is the integrated paper on both application and development of theory (125 pages).
Full Paper (for paid readers):