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A Performance Comparison Between Cross-Sectional Stochastic Dominance and Traditional Event Study Methodologies

A Performance Comparison Between Cross-Sectional Stochastic Dominance and Traditional Event Study... In this study, the performance of cross-sectional stochastic dominance (SD), first proposed by Falk and Levy (FL) (1989), is compared with three traditional event study methodologies: the Mean Adjusted model, the Market Adjusted model, and the Market and Risk Adjusted Returns model. The comparison technique we use is a simulations approach similar to that of Brown and Warner (BW) (1980). BW show that the Mean Adjusted and Market Adjusted Returns models perform as well as the more sophisticated Market and Risk Adjusted Returns model. FL, however, provide a very compelling argument against the three traditional event study methodologies. The problem, they note, is not the theoretical need for risk adjustment; it is the definition and measurement of risk. FL assert that the observed abnormal returns (or lack thereof) may be due to omitted variables, a market proxy effect, or other specification errors in implementing the traditional event study methodologies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

A Performance Comparison Between Cross-Sectional Stochastic Dominance and Traditional Event Study Methodologies

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References (13)

Publisher
Springer Journals
Copyright
Copyright © 1999 by 1999 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
DOI
10.1023/A:1008376819903
Publisher site
See Article on Publisher Site

Abstract

In this study, the performance of cross-sectional stochastic dominance (SD), first proposed by Falk and Levy (FL) (1989), is compared with three traditional event study methodologies: the Mean Adjusted model, the Market Adjusted model, and the Market and Risk Adjusted Returns model. The comparison technique we use is a simulations approach similar to that of Brown and Warner (BW) (1980). BW show that the Mean Adjusted and Market Adjusted Returns models perform as well as the more sophisticated Market and Risk Adjusted Returns model. FL, however, provide a very compelling argument against the three traditional event study methodologies. The problem, they note, is not the theoretical need for risk adjustment; it is the definition and measurement of risk. FL assert that the observed abnormal returns (or lack thereof) may be due to omitted variables, a market proxy effect, or other specification errors in implementing the traditional event study methodologies.

Journal

Review of Quantitative Finance and Accounting – Springer Journals

Published: Oct 15, 2004

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