The role of data limitations,seasonality and frequency in asset pricing models |
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| Authors: | Irina Murtazashvili Nadia Vozlyublennaia |
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| Institution: | 1. Department of Economics, University of Pittsburgh, Pittsburgh, PA 15260, United States;2. Area of Finance, Rawls College of Business Administration, Texas Tech University, Lubbock, TX 79409-2101, United States;1. University of Stirling, Stirling Management School, Accounting and Finance Division, FK9 4LA, Scotland, UK;2. University of Liverpool, University of Liverpool Management School, Chatham Building, Chatham Street, Liverpool, L69 7ZH, UK;3. University of Glasgow, Adam Smith Business School, West Quadrangle, Main Building, Room G683, University Avenue, Glasgow, G12 8QQ, Scotland, UK;1. Department of Finance, College of Business Administration, BSN 3403, University of South Florida, Tampa, FL 33620, USA;2. Barowsky School of Business, Dominican University of California, 50 Acacia Ave, San Rafael, CA 94901, USA |
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| Abstract: | We demonstrate that the estimates of the Capital Asset Pricing Model (CAPM) parameters significantly differ across samples, which are based on different days of the week (representing different seasons). Our evidence suggests that the “noise” in the data is not an issue. We also show that parameter differences for mixed samples, which contain information on different seasons, are too small to distort statistical analysis. This is so because parameter estimates converge to some values (but not necessarily to the true values) for high frequencies or as the sample size becomes large. Our evidence suggests a possibility that the CAPM may hold empirically if seasonality in the parameters of the population model are taken into consideration. |
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