Option Pricing with Heavy-Tailed Distributions of Logarithmic Returns

TL;DR

This paper introduces a discrete-time option pricing model using truncated Student's t-distributions to better capture heavy-tailed log returns, showing good empirical fit and theoretical consistency with no-arbitrage principles.

Contribution

It develops a novel option pricing framework based on heavy-tailed distributions, specifically truncated Student's t, with a single parameter for different maturities and strikes.

Findings

Distribution support width has weak impact on prices.

Model approximately satisfies no-arbitrage and put-call parity.

Empirical results match real market data well.

Abstract

A growing body of literature suggests that heavy tailed distributions represent an adequate model for the observations of log returns of stocks. Motivated by these findings, here we develop a discrete time framework for pricing of European options. Probability density functions of log returns for different periods are conveniently taken to be convolutions of the Student's t-distribution with three degrees of freedom. The supports of these distributions are truncated in order to obtain finite values for the options. Within this framework, options with different strikes and maturities for one stock rely on a single parameter -- the standard deviation of the Student's t-distribution for unit period. We provide a study which shows that the distribution support width has weak influence on the option prices for certain range of values of the width. It is furthermore shown that such family of truncated distributions approximately satisfies the no-arbitrage principle and the put-call parity. The relevance of the pricing procedure is empirically verified by obtaining remarkably good match of the numerically computed values by our scheme to real market data.