Robert Martin

Seconding this: I'd like to have the note title as the flashcard front, and the entire note content as the flashcard back. All my notes are small and atomic, so...

In your second last comment, the error _is_ reproducible to me but also there's a problem with the code: One shouldn't call any optimisation method on the `EfficientFrontier` object before...

This is a difficult problem: see #133 for ideas

I'm not merging this for now for a couple of reasons: 1. I think there are probably much more efficient vectorised ways of computing downside deviation, something along the lines...

It's possible to do this by defining custom objective functions etc, but you may be better off just coding it up directly in `cvxpy`.

Yes, I agree. Honestly I feel that the whole compounding/log returns thing was not very well thought out. I don't think I should have added support for log returns in...

If you have clean data, the covariance matrix should not have NaNs in it... Generally one must be careful about modifying the cov matrix after its construction, because as the...

The calculation is based on an approximation of the CVaR required to solve the problem using convex optimisation. The [docs](https://pyportfolioopt.readthedocs.io/en/latest/GeneralEfficientFrontier.html#efficient-cvar) have more details on this.

I think PyPortfolioOpt is incorrect here. It is reporting the result of the optimisation problem (a problem which is equivalent to minimising CVaR), but that result is not equivalent to...

I see, but the outcome is still not equal to the actual CVaR, as computed using `returns[returns