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.

  • $\begingroup$ SABR-type models ? $\endgroup$ Commented May 27, 2014 at 17:41
  • $\begingroup$ basically you can make your stochastic volatility process whaterver you want as long as the framework remains free of arbitrage. $\endgroup$ Commented May 27, 2014 at 17:44
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    $\begingroup$ this document is interesting by itself but also introduces several stoch vol models: bfi.cl/papers/… $\endgroup$ Commented May 27, 2014 at 17:47
  • $\begingroup$ Thanks for the suggestions and thank you very much for the document, I've only looked through it so far but it looks amazingly interesting! $\endgroup$
    – htd
    Commented May 27, 2014 at 19:12
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    $\begingroup$ let me know whether you need anyhting more ;) - and spread the word about quant stack exchange :D $\endgroup$ Commented May 27, 2014 at 20:24

1 Answer 1


In my opinion, the best book on this area is Lorenzo Bergomi's "Stochastic Volatility Models" which covers the local volatility models, stochastic volatility models and local stochastic volatility models in great details with their properties and appropriateness.

His application is equities derivatives, but this would also be useful for FX. He was head of SocGen equity derivatives research for many years. SocGen is one of the most technical shop on the street.

  • $\begingroup$ Thanks for taking the time to provide the reference and a nice summary. I'm putting it high on my "books to get someday" list. I trust you way more than an amazon review. $\endgroup$
    – mark leeds
    Commented Sep 21, 2023 at 5:47

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