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Dynamic asset beta measurement

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  • Brandon Chen
  • Jonathan J. Reeves

Abstract

The recent advent of high-frequency data and advances in financial econometrics allow market participants to evaluate the accuracy of different beta (systematic risk) measurements. Benchmarking against the monthly realized beta formed by 30-minute data, we compare the popular Fama--MacBeth betas, the monthly realized betas formed by daily returns and our Hodrick--Prescott filtered betas, with the smoothing parameter, λ, set to 100. We find our filtered betas reduce the measurement error substantially relative to other beta measures. These results enable market participants to measure betas with greater precision and efficiency even with only daily returns in hand.

Suggested Citation

  • Brandon Chen & Jonathan J. Reeves, 2012. "Dynamic asset beta measurement," Applied Financial Economics, Taylor & Francis Journals, vol. 22(19), pages 1655-1664, October.
    • Handle: RePEc:taf:apfiec:v:22:y:2012:i:19:p:1655-1664
    DOI: 10.1080/09603107.2012.674203
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    Cited by:

    1. Weron, Rafał & Zator, Michał, 2015. "A note on using the Hodrick–Prescott filter in electricity markets," Energy Economics, Elsevier, vol. 48(C), pages 1-6.
    2. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    3. Xu, Jia & Tan, Xiujie & He, Gang & Liu, Yu, 2019. "Disentangling the drivers of carbon prices in China's ETS pilots — An EEMD approach," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 1-9.
    4. Papageorgiou, Nicolas & Reeves, Jonathan J. & Xie, Xuan, 2016. "Betas and the myth of market neutrality," International Journal of Forecasting, Elsevier, vol. 32(2), pages 548-558.

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