On traditional quant projects, synthetic data generation to support backtesting is becoming a common practice, there is a good summary of it in the appendix A of “Machine Learning for Asset Managers”, by Marcos Lopez de Prado.
We can use various different methods to generate synthetic data, one of the most promising ones is GANs (Generative Adversarial Networks).
I have searched for discussions on the forum about this topic but couldn’t find any, so I’m posting this to bring it up. What do you think? Could it be useful in numerai?