Stochastic volatility of the futures prices of emission allowances: A Bayesian approach

Jungmu Kim, Yuen Jung Park and Doojin Ryu

Physica A: Statistical Mechanics and its Applications, 2017, vol. 465, issue C, 714-724

Abstract: Understanding the stochastic nature of the spot volatility of emission allowances is crucial for risk management in emissions markets. In this study, by adopting a stochastic volatility model with or without jumps to represent the dynamics of European Union Allowances (EUA) futures prices, we estimate the daily volatilities and model parameters by using the Markov Chain Monte Carlo method for stochastic volatility (SV), stochastic volatility with return jumps (SVJ) and stochastic volatility with correlated jumps (SVCJ) models. Our empirical results reveal three important features of emissions markets. First, the data presented herein suggest that EUA futures prices exhibit significant stochastic volatility. Second, the leverage effect is noticeable regardless of whether or not jumps are included. Third, the inclusion of jumps has a significant impact on the estimation of the volatility dynamics. Finally, the market becomes very volatile and large jumps occur at the beginning of a new phase. These findings are important for policy makers and regulators.

Keywords: MCMC; EUA futures; Stochastic volatility; Jump model (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:465:y:2017:i:c:p:714-724

DOI: 10.1016/j.physa.2016.08.036

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