Asian Option Pricing with Orthogonal Polynomials

TL;DR

This paper introduces a novel series expansion method for pricing Asian options using orthogonal polynomials related to the log-normal distribution, providing explicit terms and convergence conditions.

Contribution

The paper develops an explicit polynomial series expansion for Asian option pricing in the Black-Scholes model, avoiding numerical integration and special functions.

Findings

Series converges under certain conditions

Bias from log-normal moment indeterminacy is negligible in practice

Method provides explicit pricing formulas

Abstract

In this paper we derive a series expansion for the price of a continuously sampled arithmetic Asian option in the Black-Scholes setting. The expansion is based on polynomials that are orthogonal with respect to the log-normal distribution. All terms in the series are fully explicit and no numerical integration nor any special functions are involved. We provide sufficient conditions to guarantee convergence of the series. The moment indeterminacy of the log-normal distribution introduces an asymptotic bias in the series, however we show numerically that the bias can safely be ignored in practice.