Jumps in energy commodity markets

Neil A. Wilmot, Charles F. Mason

Research output: Chapter in Book/Report/Conference proceedingChapter


This chapter is concernedwith the statistical behavior of energy commodity prices. Aparticularly salient feature ofmany commoditymarkets is the unexpectedly rapid changes - or jumps - that result from the arrival of new information. Such a processwould contradict the viewthat energy commodity prices followa geometric Brownian motion (GBM) process (i.e. log returns are normally distributed). That is, assuming a GBMprocess for the data-generatingmechanismwould be insufficient to capture the true dynamics of energy commodity markets. The discontinuous arrival of information necessitates a stochastic process that incorporates this feature, and as such, Jump processes have become an important tool in the analysis of energy markets. While such models allow for multiple jumps in a period, the jump intensity is assumed to be constant over time - a questionable assumption given the dynamics of such energy markets. The autoregressive conditional jump intensity (ARJI) model ofChan and Maheu [2002], which allows for a time-varying jump intensity, is applied to important energy commodity markets. The results indicate the importance of incorporating time-varying jump intensities in energy markets.

Original languageEnglish (US)
Title of host publicationHandbook of Energy Finance
Subtitle of host publicationTheories, Practices and Simulations
PublisherWorld Scientific Publishing Co.
Number of pages15
ISBN (Electronic)9789813278387
ISBN (Print)9789813278370
StatePublished - Jan 1 2020

Bibliographical note

Publisher Copyright:
© 2019 by World Scientific Publishing Co. Pte. Ltd.


  • ARJI
  • Energy commodity prices
  • Jump diffusion


Dive into the research topics of 'Jumps in energy commodity markets'. Together they form a unique fingerprint.

Cite this