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More Powerful Portfolio Approaches to Regressing Abnormal Returns on Firm‐Specific Variables for Cross‐Sectional Studies
Author(s) -
CHANDRA RAMESH,
BALACHANDRAN BALA V.
Publication year - 1992
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/j.1540-6261.1992.tb04697.x
Subject(s) - heteroscedasticity , econometrics , portfolio , ordinary least squares , regression , regression analysis , statistics , economics , mathematics , portfolio optimization , financial economics
OLS regression ignores both heteroscedasticity and cross‐correlations of abnormal returns; therefore, tests of regression coefficients are weak and biased. A Portfolio OLS (POLS) regression accounts for correlations and ensures unbiasedness of tests, but does not improve their power. We propose Portfolio Weighted Least Squares (PWLS) and Portfolio Constant Correlation Model (PCCM) regressions to improve the power. Both utilize the heteroscedasticity of abnormal returns in estimating the coefficients; PWLS ignores the correlations, while PCCM uses intra‐and inter‐industry correlations. Simulation results show that both lead to more powerful tests of regression coefficients than POLS.