What if beta is not stable? Applying the Kalman filter to risk estimates of top US companies over the long time horizon

Ewa Feder-Sempach (), Piotr Szczepocki () and Wiesław Dębski ()
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Ewa Feder-Sempach: University of Lodz, Faculty of Economics and Sociology, Department of International Finance and Investment
Piotr Szczepocki: University of Lodz, Faculty of Economics and Sociology, Department of Statistical Methods
Wiesław Dębski: University of Lodz, Faculty of Economics and Sociology

Bank i Kredyt, 2023, vol. 54, issue 1, 25-44

Abstract: The main objective of this paper is to examine the Kalman approach to estimate the time-varying CAPM beta on the US stock market over the long time horizon of thirty-one years. We investigate the beta estimates on the basis of three specifications: random walk (RW), mean-reverting process (MR), and random coefficient of the beta parameter (RC) for companies listed on NYSE and NASDAQ in the period 1990–2021. We examine the prognostic power of beta estimates and ranked the results according to criteria of forecast accuracy. In terms of the adopted criteria, the estimation of the beta parameter assuming its variability in time proved to be better than the OLS, LAD and ROLS methods of the Sharpe model. We can conclude that the Kalman filter approach with the assumption of a random coefficient (RC) or mean-reversion (MR) for the CAPM beta parameter gives the best results.

Keywords: rate of return; beta parameter; time-varying model; Kalman filter; US stock market (search for similar items in EconPapers)
JEL-codes: C22 G10 G11 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nbp:nbpbik:v:54:y:2023:i:1:p:25-44

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