Thanks for your questions. Responses inline below.
(i) Our research backtester uses monthly return data and generates monthly portfolio returns. When I tried to run Pyfolio on our output, most of the charts looked pretty wrong. Can Pyfolio work with a monthly return stream? or do we need to use daily returns?
We have made some attempts to allow specification of a duration parameter (for example, sharpe_ratio can take
period='monthly' and it should work correctly). At this point, though, it's untested and likely to not work correctly, specifically for the tear sheets. It would probably require to use the
period kwarg more consistently across the functions. We mostly use daily returns so it's unclear that we'll add that soon, but I'd definitely consider a pull request that adds it.
(ii) We are researching a global fund (primarily US + Europe), so the SPX is not a suitable index for us, and, indeed, we may use our own in-house fundamental indices as benchmarks. Is it possible to replace the S&P 500 as the benchmark index in Pyfolio?
Yes, you should be able to pass in any timeseries as
(iii) We would like to run our systems offline. Is it possible to get Pyfolio to use local files/data frames of index returns, risk free rate, fama french factors etc. rather than downloading them every time?
Yes, absolutely. As long as you have your returns in a (time) series, your positions as well as your transactions in a DataFrame, pyfolio should be able to handle it. This NB should give you an overview of how the input data must look like: https://github.com/quantopian/pyfolio/blob/master/pyfolio/examples/overview_slides.ipynb
Hope that helps, let me know if you have further questions.
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