Can you use autoregressive diffusion to generate market data?

The author explores the possibility of using autoregressive diffusion models to generate market data, specifically stock prices and trading volume. They discuss the potential benefits and challenges of this approach, including data quality, model interpretability, and the need for large amounts of training data. The author also mentions the use of techniques such as data augmentation and model ensembling to improve results.