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Time Dependence of CAPM Betas on the Choice of Interval Frequency and Return Timeframes: Is There an Optimum?

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  • Pankaj Agrrawal

    (Maine Business School, University of Maine, 5723 D. P. Corbett Business Building, Orono, ME 04469, USA)

  • Faye W. Gilbert

    (Maine Business School, University of Maine, 5723 D. P. Corbett Business Building, Orono, ME 04469, USA)

  • Jason Harkins

    (Maine Business School, University of Maine, 5723 D. P. Corbett Business Building, Orono, ME 04469, USA)

Abstract

The traditional CAPM beta is almost exclusively calculated over a return period that spans a window length of 60-months, at one-month return frequencies. It is one of the most utilized models in the asset management industry to assess systematic risk. Yet there is limited evidence to suggest that these estimation parameters are optimal. Utilizing data between January 2000 and December 2021 for the Russell 1000 index, we test daily, weekly, and monthly beta estimations to calculate tracking errors (TE) for the use of these betas in predicting subsequent performance over daily, weekly, and monthly timeframes. We identify that daily CAPM betas are best for predicting subsequent period daily returns and that weekly CAPM betas are strongly correlated with forward weekly and monthly period returns. Leveraging the significant advances in computing resources and the increasing utilization of high frequency trading strategies, we argue that additional window length and return interval-based CAPM betas should be calculated for estimating the systematic risk embedded in diversified portfolios.

Suggested Citation

  • Pankaj Agrrawal & Faye W. Gilbert & Jason Harkins, 2022. "Time Dependence of CAPM Betas on the Choice of Interval Frequency and Return Timeframes: Is There an Optimum?," JRFM, MDPI, vol. 15(11), pages 1-18, November.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:11:p:520-:d:965451
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