Numerical aspects of integration in semi-closed option pricing formulas for stochastic volatility jump diffusion models

TL;DR

This paper addresses numerical challenges in integrating functions for stochastic volatility option pricing models, proposing a regime switching algorithm to improve accuracy and efficiency in integral evaluations.

Contribution

It introduces a fast regime switching algorithm that determines when higher precision arithmetic is necessary during integral evaluation in SV models.

Findings

The proposed algorithm reduces computational time by avoiding unnecessary high-precision calculations.

It improves the accuracy of integral evaluations in problematic parameter regimes.

Recommended quadrature methods enhance robustness for various SV model parameters.

Abstract

In mathematical finance, a process of calibrating stochastic volatility (SV) option pricing models to real market data involves a numerical calculation of integrals that depend on several model parameters. This optimization task consists of large number of integral evaluations with high precision and low computational time requirements. However, for some model parameters, many numerical quadrature algorithms fail to meet these requirements. We can observe an enormous increase in function evaluations, serious precision problems and a significant increase of computational time. In this paper we numerically analyse these problems and show that they are especially caused by inaccurately evaluated integrands. We propose a fast regime switching algorithm that tells if it is sufficient to evaluate the integrand in standard double arithmetic or if a higher precision arithmetic has to be used. We compare and recommend numerical quadratures for typical SV models and different parameter values, especially for problematic cases.