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Jump Processes in the Market for Crude Oil

In many commodity markets, the arrival of new information leads to unexpectedly rapid changes--or jumps--in commodity prices. Such arrivals suggest the assumption that log-return relatives are normally distributed may not hold. Combined with time-varying volatility, the possibility of jumps offers a potential explanation for fat tails in oil price returns. This article investigates the potential presence of jumps and time-varying volatility in the spot price of crude oil and in futures prices. The investigation is carried out over three data frequencies (Monthly, Weekly, Daily), which allows for an investigation of temporal properties. Employing likelihood ratio tests to compare among four stochastic data-generating processes, we find that that allowing for both jumps and time-varying volatility improves the model's ability to explain spot prices at each level of temporal aggregation; this combination also provides a statistically compelling improvement in model fit for futures prices at the Daily and Weekly level. At the monthly level, allowing for jumps does not provide a statistically significant increase in model fit after incorporating time-varying volatility into the model.

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Energy Specializations: Petroleum – Markets and Prices for Crude Oil and Products; Energy Modeling – Energy Data, Modeling, and Policy Analysis

JEL Codes: C58: Financial Econometrics, Q31: Nonrenewable Resources and Conservation: Demand and Supply; Prices, C52: Model Evaluation, Validation, and Selection, Q35: Hydrocarbon Resources, Q02: Commodity Markets

Keywords: Crude Oil prices, Jump diffusion, GARCH

DOI: 10.5547/01956574.34.1.2

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Published in Volume 34, Number 1 of the bi-monthly journal of the IAEE's Energy Economics Education Foundation.


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