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

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 t...

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Bibliographic Details
Published in:Review of quantitative finance and accounting 1999-03, Vol.12 (2), p.103-112
Main Authors: Larsen, Glen A, Resnick, Bruce G
Format: Article
Language:English
Subjects:
Abnormal returns
Capital assets
Comparative analysis
Earnings
Economic performance
Efficiency
Efficient markets
Expected utility
Methodology
Methods
Portfolio performance
Portfolio selection
Rates of return
Securities markets
Statistics
Stochastic models
Stochastic processes
Stock returns
Studies
Citations: Items that cite this one
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Summary: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. The present research finds that SD analysis without the bootstrap method for statistical testing is not very useful at any level of abnormal return. However, when the bootstrap method of statistical testing is employed, SD is found to perform as well as, and sometimes better than, the three traditional models in detecting simulated abnormal performance at all test levels.
ISSN:0924-865X
1573-7179
DOI:10.1023/a:1008376819903