Valuing the quality option in agricultural commodity futures: a Monte Carlo simulation based approach

TL;DR

This paper presents a Monte Carlo simulation method, enhanced with antithetic variables, to value quality options in agricultural commodity futures, aiding in understanding their impact on contract pricing and hedging performance.

Contribution

It introduces a novel Monte Carlo simulation approach with variance reduction techniques for valuing quality options in commodity futures.

Findings

Efficient valuation of quality options using Monte Carlo simulation.

Antithetic variables improve simulation accuracy and efficiency.

Provides insights into how quality options affect futures pricing.

Abstract

Agricultural commodity futures are often settled by delivery. Quality options that allow the futures short to deliver one of several underlying assets are commonly used in such contracts to prevent manipulation. Inclusion of these options reduces the price of the futures contract and leads to degraded contract hedging performance. Valuation of these options is a first step in assessing the impact of the quality options embedded into a futures contract. This paper demonstrates a Monte Carlo simulation based approach to estimate the value of a quality option. In order to improve simulation efficiency, the technique of antithetic variables is used. This approach can help in the assessment of the impact of embedded quality options.