Fast and Simple Method for Pricing Exotic Options using Gauss-Hermite Quadrature on a Cubic Spline Interpolation

TL;DR

This paper introduces a simple, robust, and efficient numerical method for pricing exotic options using Gauss-Hermite quadrature on cubic spline interpolation, offering accuracy comparable to advanced finite difference methods with faster computation.

Contribution

The paper presents a novel explicit algorithm that combines Gauss-Hermite quadrature with cubic spline interpolation for efficient exotic option pricing, outperforming traditional methods in speed while maintaining accuracy.

Findings

The method achieves accuracy comparable to advanced finite difference algorithms.

It significantly reduces computation time compared to Monte Carlo and finite difference methods.

The approach is versatile, applicable to various path-dependent options like Asian options and variable annuities.

Abstract

There is a vast literature on numerical valuation of exotic options using Monte Carlo, binomial and trinomial trees, and finite difference methods. When transition density of the underlying asset or its moments are known in closed form, it can be convenient and more efficient to utilize direct integration methods to calculate the required option price expectations in a backward time-stepping algorithm. This paper presents a simple, robust and efficient algorithm that can be applied for pricing many exotic options by computing the expectations using Gauss-Hermite integration quadrature applied on a cubic spline interpolation. The algorithm is fully explicit but does not suffer the inherent instability of the explicit finite difference counterpart. A `free' bonus of the algorithm is that it already contains the function for fast and accurate interpolation of multiple solutions required by many discretely monitored path dependent options. For illustrations, we present examples of pricing a series of American options with either Bermudan or continuous exercise features, and a series of exotic path-dependent options of target accumulation redemption note (TARN). Results of the new method are compared with Monte Carlo and finite difference methods, including some of the most advanced or best known finite difference algorithms in the literature. The comparison shows that, despite its simplicity, the new method can rival with some of the best finite difference algorithms in accuracy and at the same time it is significantly faster. Virtually the same algorithm can be applied to price other path-dependent financial contracts such as Asian options and variable annuities.