Work

Linking Path-Dependent and Stochastic Volatility Models

Year: 2025

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2510.02024

Authors: Cohen, Samuel N., Svosve, Cephas

Institutions: University of Oxford, Mathematical Institute of the Slovak Academy of Sciences

Language: English

Topic: Stochastic processes and financial applications

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funder: University of Oxford

OpenAlex ID: W4414820349

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