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 ? $\endgroup$ – Probilitator May 27 '14 at 17:41
  • $\begingroup$ basically you can make your stochastic volatility process whaterver you want as long as the framework remains free of arbitrage. $\endgroup$ – Probilitator May 27 '14 at 17:44
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    $\begingroup$ this document is interesting by itself but also introduces several stoch vol models: bfi.cl/papers/… $\endgroup$ – Probilitator May 27 '14 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! $\endgroup$ – Henrik May 27 '14 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 $\endgroup$ – Probilitator May 27 '14 at 20:24

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