GENERALIZED HEDGE RATIO ESTIMATION WITH AN UNKNOWN MODEL

Jeffrey Dorfman () and Dwight R. Sanders

No 19024, 2004 Conference, April 19-20, 2004, St. Louis, Missouri from NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management

Abstract: Myers and Thompson (1989) pioneered the concept of a generalized approach to estimating hedge ratios, pointing out that the model specification could have a large impact on the hedge ratio estimated. While a huge empirical literature exists on estimating hedge ratios, the literature is lacking a formal treatment of model specification uncertainty. This research accomplishes that task by taking a Bayesian approach to hedge ratio estimation, where specification uncertainty is explicitly modeled. Specifically, we present a Bayesian approach to hedge ratio estimation that integrates over model specification uncertainty, yielding an optimal hedge ratio estimator that is robust to possible model specification because it is an average across a set of hedge ratios conditional on di erent models. Model specifications vary by exogenous variables (such as exports, stocks, and interest rates) and lag lengths included. The methodology is applied to data on corn and soybeans and results show the potential benefits and insights gained from such an approach.

Keywords: Marketing (search for similar items in EconPapers)
Pages: 19
Date: 2004
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https://ageconsearch.umn.edu/record/19024/files/cp04do01.pdf (application/pdf)

Related works:
Working Paper: Generalized Hedge Ratio Estimation with an Unknown Model (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:ncrfou:19024

DOI: 10.22004/ag.econ.19024

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