The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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More Powerful Portfolio Approaches to Regressing Abnormal Returns on Firm‐Specific Variables for Cross‐Sectional Studies
Published: 12/01/1992 | DOI: 10.1111/j.1540-6261.1992.tb04697.x
RAMESH CHANDRA, BALA V. BALACHANDRAN
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.
A Portfolio Approach to Estimating the Average Correlation Coefficient for the Constant Correlation Model
Published: 12/01/1989 | DOI: 10.1111/j.1540-6261.1989.tb02664.x
YASH P. ANEJA, RAMESH CHANDRA, ERDAL GUNAY
This paper presents a portfolio approach to estimating the average correlation coefficient of a group of stocks which are considered for portfolio analysis. The average correlation coefficient has been shown to produce a better estimate of the future correlation matrix than individual pairwise correlations. The advantage of the approach described here is that it does not require the estimation of pairwise correlations for estimating their average.