In the CQF, we learned about GARCH etc. I assume this is somewhat 'entry level' and that there are a wide variety of other mechanisms for pricing volatility and options based (ONLY) on historical price data.
I have been doing quite a bit of investigation on using machine learning to price puts and calls based only on past data. This seems to hold up well.
I am curious to know what other families of solutions quants have pursued in this area? Obviously I'm not asking for anything proprietary, but more a feel as to where the research is being focused and what types of algorithms are currently popular (beyond the ARCHs).