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Dynamics of Biofuel Stock Prices: A Bayesian Approach

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Abstract

We use Bayesian Markov Chain Monte Carlo methods to investigate the linkage between the volatility of ethanol security prices and the uncertainty surrounding the profitability of ethanol production and the price variations of non-ethanol energy securities. The joint evolution of return and volatility is modeled as a stochastic process that incorporates jumps in both return and volatility. While a strong and significant correlation is found between the volatility of ethanol securities and profit uncertainty from June 2005 to July 2008, the dynamic pattern of ethanol stock volatility is strikingly similar to that of the S&P 500 energy sector index in the more recent period. Our evidence lends support to the findings in the literature on rational learning from uncertainty in determining the equity price and volatility during the adoption and development of a technological innovation.

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Paper provided by Center for Agricultural and Rural Development (CARD) at Iowa State University in its series Center for Agricultural and Rural Development (CARD) Publications with number 09-wp498.

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Date of creation: Sep 2009
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Handle: RePEc:ias:cpaper:09-wp498

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Keywords: jumps; rational learning; stochastic volatility; technological innovation.;

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Cited by:
  1. Khalfaoui Rabeh, K & Boutahar Mohamed, B, 2011. "A time-scale analysis of systematic risk: wavelet-based approach," MPRA Paper 31938, University Library of Munich, Germany.

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