Explicit approximations of option prices via Malliavin calculus in a general stochastic volatility framework

TL;DR

This paper develops explicit approximation formulas for European put options in a general stochastic volatility framework using Malliavin calculus, enabling efficient pricing and calibration.

Contribution

It introduces a novel Malliavin calculus-based expansion for option prices in a general stochastic volatility model with explicit error bounds.

Findings

Approximation formulas are explicit and computationally efficient.

Error bounds are derived and depend on volatility process moments.

Numerical analysis shows errors are acceptable for practical applications.

Abstract

We establish an explicit approximation formula for European put option prices within a general stochastic volatility model with time-dependent parameters. Our methodology is based on expansions of the mixing representation of the put option price as an expectation of the Black-Scholes formula, in which the resulting terms are calculated explicitly by Malliavin calculus. We obtain an explicit representation of the error generated by the expansion procedure, and bound it in terms of moments of functionals of the underlying volatility process. Under the assumption of piecewise-constant parameters, our approximation formulas become closed-form, and compatible with a proposed fast calibration scheme. Finally, we perform a numerical sensitivity analysis to investigate the quality of our approximation formula in the so-called Stochastic Verhulst model, and show that the errors are well within the acceptable range for application purposes.