Citations (35)



Performance Evaluation with Transactions Data: the Stock Selection of Investment Newsletters

Andrew Metrick

Yale School of Management; National Bureau of Economic Research (NBER)

July 1998

NBER Working Paper No. w6648

This paper analyzes the equity-portfolio recommendations made by investment newsletters. The dataset spans 17 years, is free of survivor and back-fill biases, and includes the complete recommendations for 153 different newsletters. Overall, there is no significant evidence of superior stock-picking ability for this sample of newsletters. Some individual letters do have superior performance records, but this does not occur more often than would be expected by chance, and these records are never more extreme than would be expected for the sample size. In addition, a strategy of buying past winners does not earn positive abnormal returns. The comprehensive and bias-free transactions database also allows for insights into several popular models of performance evaluation. The transactions-based approach of Daniel, Grinblatt, Titman and Wermers (1997) yields a median improvement in precision of 10 percent over the 4-factor model of Carhart (1997a), with the former approach providing more precise estimates of abnormal performance for more than 80 percent of the newsletters. This compares with a median improvement of less than 1 percent for the 4-factor model over the CAPM.

Number of Pages in PDF File: 52

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Date posted: July 19, 2000  

Suggested Citation

Metrick, Andrew, Performance Evaluation with Transactions Data: the Stock Selection of Investment Newsletters (July 1998). NBER Working Paper No. w6648. Available at SSRN: https://ssrn.com/abstract=226352

Contact Information

Andrew Metrick (Contact Author)
Yale School of Management ( email )
165 Whitney Avenue
New Haven, CT 06511
United States
(203)-432-3069 (Phone)
HOME PAGE: http://faculty.som.yale.edu/andrewmetrick/

National Bureau of Economic Research (NBER) ( email )
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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