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A Jump Diffusion Model for Agricultural Commodities with Bayesian Analysis
Author(s) -
Schmitz Adam,
Wang Zhiguang,
Kimn JungHan
Publication year - 2014
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.21597
Subject(s) - economics , futures contract , econometrics , markov chain monte carlo , stochastic volatility , volatility (finance) , bayesian probability , jump diffusion , jump , financial economics , mathematics , statistics , physics , quantum mechanics
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