The Empirical Minimum-Variance Hedge
Sergio Lence and
Dermot Hayes
American Journal of Agricultural Economics, 1994, vol. 76, issue 1, 94-104
Abstract:
Decision making under unknown true parameters (estimation risk) is discussed along with Bayes' and parameter certainty equivalent (PCE) criteria. Bayes' criterion incorporates estimation risk in a manner consistent with expected utility maximization. The PCE method, which is the most commonly used, is not consistent with expected utility maximization. Bayes' criterion is employed to solve for the minimum-variance hedge ratio. Empirical application of Bayes' minimum-variance hedge ratio is addressed and illustrated. Simulations show that discrepancies between prior and sample parameters may lead to substantial differences between Bayesian and PCE minimum-variance hedges.
Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://hdl.handle.net/10.2307/1243924 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Empirical Minimum-Variance Hedge (The) (1994) 
Working Paper: The Empirical Minimum-Variance Hedge (1994) 
Working Paper: Empirical Minimum Variance Hedge, The (1993) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:76:y:1994:i:1:p:94-104.
Access Statistics for this article
American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu
More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().