The Bayesian Methods of Jump Detection: The Example of Gas and EUA Contract Prices

Maciej Kostrzewski ()
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Maciej Kostrzewski: Cracow University of Economics

Central European Journal of Economic Modelling and Econometrics, 2019, vol. 11, issue 2, 107-131

Abstract: In the paper we present and apply a Bayesian jump-diffusion model and stochastic volatility models with jumps. The problem of how to classify an observation as a result of a jump is addressed, under the Bayesian approach, by introducing latent variables. The empirical study is focused on the time series of gas forward contract prices and EUA futures prices. We analyse the frequency of jumps and relate the moments in which jumps occur to calendar effects or political and economic events and decisions. The calendar effects explain many jumps in gas contract prices. The single jump is identified in the EUA futures prices under the SV-type models. The jump is detected on the day the European Parliament voted against the European Commission’s proposal of backloading. The Bayesian results are compared with the outcomes of selected non-Bayesian techniques used for detecting jumps.

Keywords: jump; jump-diffusion model; stochastic volatility; double exponential distribution; commodity markets (search for similar items in EconPapers)
JEL-codes: C51 C53 C58 Q41 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:psc:journl:v:11:y:2019:i:2:p:107-131

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