Pricing Carbon Allowance Options on Futures: Insights from High-Frequency Data

TL;DR

This paper introduces a novel multifactor stochastic volatility model with jumps for pricing carbon allowance options, utilizing high-frequency data to estimate risk premia and analyze market dynamics.

Contribution

It is the first to estimate equity and variance risk premia in the carbon futures option market using high-frequency data and a multifactor stochastic volatility framework.

Findings

Estimated equity and variance risk premia for carbon options.

Provided a detailed model of futures price, volatility, and jump dynamics.

Gained insights into daily market behavior from tick-by-tick data.

Abstract

Leveraging a unique dataset of carbon futures option prices traded on the ICE market from December 2015 until December 2020, we present the results from an unprecedented calibration exercise. Within a multifactor stochastic volatility framework with jumps, we employ a three-dimensional pricing kernel compensating for equity and variance components' risk to derive an analytically tractable and numerically practical approach to pricing. To the best of our knowledge, we are the first to provide an estimate of the equity and variance risk premia for the carbon futures option market. We gain insights into daily option and futures dynamics by exploiting the information from tick-by-tick futures trade data. Decomposing the realized measure of futures volatility into continuous and jump components, we employ them as auxiliary variables for estimating futures dynamics via indirect inference. Our approach provides a realistic description of carbon futures price, volatility, and jump dynamics and an insightful understanding of the carbon option market.