Dynamics of Biofuel Stock Prices: A Bayesian Approach
AbstractWe 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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Bibliographic InfoArticle provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.
Volume (Year): 93 (2010)
Issue (Month): 2 ()
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Other versions of this item:
- Du, Xiaodong & Hayes, Dermot J. & Yu, Cindy, 2010. "Dynamics of Biofuel Stock Prices: A Bayesian Approach," Staff General Research Papers 31533, Iowa State University, Department of Economics.
- Xiaodong Du & Dermot J. Hayes & Cindy L. Yu, 2009. "Dynamics of Biofuel Stock Prices: A Bayesian Approach," Center for Agricultural and Rural Development (CARD) Publications 09-wp498, Center for Agricultural and Rural Development (CARD) at Iowa State University.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
- Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
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- 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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