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Re-evaluating hedging performance
Author(s)
Date Issued
2005-07-24
Date Available
2009-05-27T11:51:07Z
Abstract
Mixed results have been documented for the performance of hedging strategies using futures. This paper reinvestigates this issue using an extensive set of performance evaluation metrics across seven international markets. We compare the hedging performance of short and long
hedgers using traditional variance based approaches together with modern risk management techniques including Value at Risk, Conditional Value at Risk and approaches based on Downside Risk. Our findings indicate that using these metrics to evaluate hedging performance, yields differences in terms of best hedging strategy as compared with the traditional variance measure. We also find significant differences in performance between short and long hedgers. These results are observed both in-sample and out-of-sample.
hedgers using traditional variance based approaches together with modern risk management techniques including Value at Risk, Conditional Value at Risk and approaches based on Downside Risk. Our findings indicate that using these metrics to evaluate hedging performance, yields differences in terms of best hedging strategy as compared with the traditional variance measure. We also find significant differences in performance between short and long hedgers. These results are observed both in-sample and out-of-sample.
Sponsorship
University College Dublin. Faculty of Commerce
Type of Material
Working Paper
Publisher
University College Dublin. School of Business. Centre for Financial Markets
Series
Centre for Financial Markets working paper series
WP-05-03
Copyright (Published Version)
Centre for Financial Markets, 2005
Classification
G10
G12
G15
Subject – LCSH
Hedging (Finance)--Evaluation
Financial futures--Evaluation
Risk--Econometric models
Analysis of variance
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
File(s)
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WP-05-03.pdf
Size
187.05 KB
Format
Adobe PDF
Checksum (MD5)
7bf7316c0b05bef2bc3d63bce454dc8c
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