Time-Variations in Commodity Price Jumps
32 Pages Posted: 10 Aug 2013 Last revised: 22 Mar 2019
Date Written: February 20, 2015
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 20 years 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
JEL Classification: G13, G17
Suggested Citation: Suggested Citation