Robust and Partially Adaptive Estimation of Regression Models

Robust and Partially Adaptive Estimation of Regression Models

It is well known that least squares estimates can be very sensitive to departures from normality. Various robust estimators such as least absolute deviations (LAD), Lp estimators provide possible alternatives to least squares when such departures occur. This paper applies a partially adaptive techni...

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Veröffentlicht in:The review of economics and statistics 1990-05, Vol.72 (2), p.321-327
Hauptverfasser: Butler, Richard J., McDonald, James B., Nelson, Ray D., White, Steven B.
Format: Artikel
Sprache:eng
Schlagworte:
Adaptability
Bleeding time
Common stock
Economic models
Economic statistics
Economic theory
Estimating techniques
Estimation methods
Estimators
Gaussian distributions
Least squares
Market portfolios
Mathematical independent variables
Maximum likelihood estimation
Outliers
Regression analysis
Securities markets
Stock prices
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Beschreibung
Zusammenfassung:It is well known that least squares estimates can be very sensitive to departures from normality. Various robust estimators such as least absolute deviations (LAD), Lp estimators provide possible alternatives to least squares when such departures occur. This paper applies a partially adaptive technique to estimate the parameters of Sharpe's market model. This methodology is based on a generalized t-distribution and includes as special cases least squares, LAD, Lp as well as some estimation procedures which have bounded and redescending influence functions.
ISSN:0034-6535
1530-9142
DOI:10.2307/2109722