Linking Path-Dependent and Stochastic Volatility Models
By: Samuel N. Cohen, Cephas Svosve
Potential Business Impact:
Makes stock price predictions more accurate.
We explore a link between stochastic volatility (SV) and path-dependent volatility (PDV) models. Using assumed density filtering, we map a given SV model into a corresponding PDV representation. The resulting specification is lightweight, improves in-sample fit, and delivers robust out-of-sample forecasts. We also introduce a calibration procedure for both SV and PDV models that produces standard errors for parameter estimates and supports joint calibration of SPX/VIX smile.
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