I am testing the performance difference between 2 portfolio strategies. I use Monte Carlo simulation in R to generate $N$ simulations of portfolio returns for each strategy. I then compute the Sharpe ratio for each simulation. In the end, each strategy has $N$ observations of Sharpe ratios.
How would I best go about using this data to test whether the true Sharpe ratio of one strategy is greater than that of the other?
All the research I have looked at examines comparisons between samples of returns, and not samples of Sharpe Ratios. The SharpeR package also only seems to have functions that take samples of returns as inputs.
I am also a little unsure of whether my question is even correctly stated - i.e. whether I should instead be asking about whether the true mean Sharpe ratio of one strategy is greater than that of the other.
sr_unpaired_testwill test samples of Sharpe ratios, but I am in the process of deprecating it. For your problem, if the Sharpes are over equal sample sizes, you can compute their means, then use the normal approximation and the usual standard error. $\endgroup$
sr_unpaired_testbe used to compare two samples of sharpe ratios, or is it only for one-sample tests? The documentation seems to imply the latter. $\endgroup$