I'm fiddling with estimation of stochastic volatility models and have build up a somewhat flexible framework using indirect inference.
I would like to try and throw a lot of different continuous time models into it and see how it performs. I only need it to be reasonable easy to simulate and not have to many parameters.
I know of Heston type models (i.e. square root processes) and the CEV type processes with and without mean reversion. Multifactor is an option but generally the fewer parameters the easier for me (as always).
Hope to get your input, thanks.