The section on generative machine learning methods for market simulation is finished.

It introduces both time series variational autoencoders (VAEs) and generative adversarial networks (GANs).

Since this field is still in its infancy, there are many misunderstandings that this section clarifies. It also shares my experiences with these methods.

The Portfolio Construction and Risk Management book is nearly complete, with only the sections on simulation evaluation and tail risk hedging remaining.

How much time and effort I can put into the remaining parts and thus reveal is directly proportional to the support the book receives.

If you still do not have access to the book and its Python code, see how you get it in the comments.

You will probably find it well worth it :-)