Stock Returns, Efficiency of Beta and the Probability to Grow at an Above-Average Rate Relative to the Market: Evidence from a Logit Model
Ricardo Goulart Serra, Luiz Paulo Lopes Fávero, Roy Martelanc

Abstract
Does the beta help to distinguish between companies that would gain an above or below-market return? Using logistic regression models, this paper aims to verify what characteristics help to determine the probability that stock prices will grow above market on a day of considerable market growth. The selected day was October 13th 2008, when S&P 500 achieved the largest growth (11.6%) since 1950. The analysis considered 461 companies listed on NYSE. The logistic analysis identified that the lagged return of 3 months and illiquidity are significant variables to determine the desired probability. This model would have classified correctly, a posteriori, 73.3%. On the other hand, the beta correctly classified not even 50% of observations.

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