Robert Martin

Really sorry for the slow response. HRP essentially works as follows: 1. Compute a distance matrix from the covariance matrix 2. Form hierarchical clusters based on the distance matrix 3....

Hi @x829901, Unfortunately that isn't currently possible. Risk contribution / risk parity is not a convex problem in general, though for simple constraints there is an equivalent convex problem (see...

Hi @kayuksel, Thanks for the suggestion! I'm afraid I don't understand the comment on L2 regularisation. The idea behind L2 regularisation in PyPortfolioOpt is to make the portfolios *less* sparse...

No worries, you certainly bring up a valid feature request! Part of the reason why haven't implemented any sparsity stuff is that I don't want to encourage people to use...

I wonder whether there's a quick solution involving CVXPY's [built-in entropy atom](https://www.cvxpy.org/examples/applications/max_entropy.html)

Hi Jarrod, Thanks for the suggestion! Hopefully will find some time towards the end of summer to investigate further. I like that you have a cvxpy implementation in addition to...

Check out simfin.com or stockrow.com

Hi @Imtrollin, I don't have the bandwidth to implement any new features unfortunately. However, provided you can get data into the same format as `keystats.csv` etc, you should be able...

Hi @lefig, Thanks for reaching out! Your question presupposes that with enough data, the classifier will be viable. I realise that the readme is quite encouraging in that regard, but...

@lefig I don't want to insinuate that fundamentals are useless. In fact, I've been playing around on quantopian lately and have found a couple of fundamental factors that I think...