On Calibrating Stochastic Volatility Models with time-dependent Parameters

TL;DR

This paper introduces a hybrid optimization approach for calibrating stochastic volatility models with piecewise constant parameters to market data, demonstrating numerical effectiveness and proposing future improvements.

Contribution

It presents a novel hybrid calibration algorithm for stochastic volatility models with time-dependent parameters, enhancing fitting accuracy to volatility surfaces.

Findings

Effective numerical calibration results

Potential for improved calibration procedures

Applicability to volatility surface fitting

Abstract

We consider stochastic volatility models using piecewise constant parameters. We suggest a hybrid optimization algorithm for fitting the models to a volatility surface and provide some numerical results. Finally, we provide an outlook on how to further improve the calibration procedure.