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Time-variations in commodity price jumps

Laszlo Diewald, Marcel Prokopczuk () and Chardin Wese Simen

Journal of Empirical Finance, 2015, vol. 31, issue C, 72-84

Abstract: In this paper, we study jumps in commodity prices. Unlike assumed in existing models of commodity price dynamics, a simple analysis of the data reveals that the probability of tail events is not constant but depends on the time of the year, i.e. exhibits seasonality. We propose a stochastic volatility jump–diffusion model to capture this seasonal variation. Applying the Markov Chain Monte Carlo (MCMC) methodology, we estimate our model using 20years of futures data from four different commodity markets. We find strong statistical evidence to suggest that our model with seasonal jump intensity outperforms models featuring a constant jump intensity. To demonstrate the practical relevance of our findings, we show that our model typically improves Value-at-Risk (VaR) forecasts.

Keywords: Commodities; Jump frequency; Seasonality; Markov Chain Monte Carlo (search for similar items in EconPapers)
JEL-codes: G13 G17 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1016/j.jempfin.2015.02.004

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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