Abstract
Depending on their location, outliers in returns can substantially bias ordinary least-squares estimates of beta. We introduce a new beta estimate that is resistant to outliers that cause the most bias in OLS estimates but produces estimates similar to OLS for outlier-free data. The outlier-resistant beta is an intuitively appealing weighted least-squares estimate with data-dependent weights. We show that the resistant beta is a better predictor of future risk and return characteristics than is the OLS beta in the presence of outliers and is, therefore, a valuable complement to the OLS beta. Our analysis reveals thai small companies' betas are most susceptible to outliers.
Original language | English (US) |
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Pages (from-to) | 56-69 |
Number of pages | 14 |
Journal | Financial Analysts Journal |
Volume | 59 |
Issue number | 5 |
DOIs | |
State | Published - Jan 1 2003 |
All Science Journal Classification (ASJC) codes
- Accounting
- Finance
- Economics and Econometrics