We thank the Editor (Bob Webb), two anonymous reviewers, Thomas Barkley, Philip Garcia, and Marcel Prokopczuk for their thoughtful suggestions that greatly improve the study. We appreciate the comments from the Midwest Finance Association 2012 Annual meeting in New Orleans, LA, the NCCC-134 2012 conference in St. Louis, MO, and the Financial Management Association 2012 Annual meeting in Atlanta, GA. We acknowledge the financial support from Agricultural Experiment Station at South Dakota State University (Project H363-10) and Stahly Scholar in Financial Economics. We are also grateful for the dedicated support from the High Performance Computing team at South Dakota State University.
A Jump Diffusion Model for Agricultural Commodities with Bayesian Analysis
Article first published online: 15 FEB 2013
© 2013 Wiley Periodicals, Inc.
Journal of Futures Markets
Volume 34, Issue 3, pages 235–260, March 2014
How to Cite
Schmitz, A., Wang, Z. and Kimn, J.-H. (2014), A Jump Diffusion Model for Agricultural Commodities with Bayesian Analysis. J. Fut. Mark., 34: 235–260. doi: 10.1002/fut.21597
- Issue published online: 29 JAN 2014
- Article first published online: 15 FEB 2013
- Manuscript Accepted: 1 DEC 2012
- Manuscript Received: 1 DEC 2011
Stochastic volatility, price jumps, seasonality, and stochastic cost of carry have been included separately, but not collectively, in pricing models of agricultural commodity futures and options. We propose a comprehensive model that incorporates all four features. We employ a special Markov chain Monte Carlo algorithm, new in the agricultural commodity derivatives pricing literature, to estimate the proposed stochastic volatility (SV) and stochastic volatility with jumps (SVJ) models. Overall model fitness tests favor the SVJ model. The in-sample and out-of-sample pricing results for corn, soybeans and wheat generally, with few exceptions, lend support for the SVJ model. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:235–260, 2014