Robert Martin

Hey – I skimmed through the notebook and it all looks fine?

Hi, could you clarify what you mean? You can set a minimum weight threshold in the `EfficientFrontier` constructor, or you can add weight constraints by asset using `ef.add_constraint(w[7] >0.00025`.

Adding constraints is generally the best way of doing this

Gotta be honest, this is a bit beyond me! I've never had to deal with portfolios of more than a few hundred assets.

Possibly caused by infinities in your returns data. Or maybe HBTC and BTC are similar enough to blow up the linear algebra?

Thanks for sharing the colab. I've found the problem: all your expected returns are negative! For `max_sharpe` to work, at least one of the assets must have a return greater...

Glad it worked I'm gonna leave this open so that I remember to make pypfopt raise a warning in this scenario

Hi, unfortunately not. Multi-period optimisation is a very technical area dominated by professional solutions. Realistically, I don't have the expertise or time to implement it :(

I can't reproduce this: it works for me

Do you know if it fails in every iteration of the loop? Or only in some. You can find out by doing a `try/except` within the loop. I suggest you...