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Dynamic Programming Applications in Finance

Journal of Finance 1971 26(2), 473
Edwin J. Elton, Martin J. Gruber, Dynamic Programming Applications in Finance, The Journal of Finance, Vol. 26, No. 2, Papers and Proceedings of the Twenty-Ninth Annual Meeting of the American Finance Association Detroit, Michigan December 28-30, 1970 (May, 1971), pp. 473-506

Holdings Data, Security Returns, and the Selection of Superior Mutual Funds

Journal of Financial and Quantitative Analysis 2011 46(2), 341-367
In this paper we show that selecting mutual funds using alpha computed from a fund’s holdings and security betas produces better future alphas than selecting funds using alpha computed from a time-series regression on fund returns. This is true whether future alphas are computed using holdings and security betas or a time-series regression on fund returns. Furthermore, we show that the more frequently the holdings data are available, the greater the benefit. This has major implications for the Securities and Exchange Commission’s recent ruling on the frequency of holdings disclosure and the information plan sponsors should collect from portfolio managers. We also explore the effect of conditioning betas on macroeconomic variables as suggested by Ferson and Schadt (1996) to identify superior-performing mutual funds as well as the alternative way of employing holdings data proposed by Grinblatt and Titman (1993).

Professional Expectations: Accuracy and Diagnosis of Errors

Journal of Financial and Quantitative Analysis 1984 19(4), 351
The purpose of this paper is to analyze the errors made by professional forecasters (analysts) in estimating earnings per share for a large number of firms over a number of years. We have demonstrated in a previous paper that consensus (average) estimates of earnings per share play a key role in share price determination. In this paper, we examine consensus estimates with respect to the following questions: (1) What is the size and pattern of analysts' errors? (2) What is the source of errors? (3) Are some firms more difficult to predict than others? (4) Is there an association between errors in forecasts and divergence of analysts' estimates?