### Abstract

Original language | English |
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Pages (from-to) | 531-539 |

Journal | Mathematics and Computers in Simulation |

Volume | 48 |

DOIs | |

Publication status | Published - 1999 |

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### Cite this

*Mathematics and Computers in Simulation*,

*48*, 531-539. https://doi.org/10.1016/S0378-4754(99)00033-6

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*Mathematics and Computers in Simulation*, vol. 48, pp. 531-539. https://doi.org/10.1016/S0378-4754(99)00033-6

**Time-varying estimates of CAPM betas.** / Groenewold, Nicolaas; Fraser, P.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Time-varying estimates of CAPM betas

AU - Groenewold, Nicolaas

AU - Fraser, P.

PY - 1999

Y1 - 1999

N2 - It is well known that the CAPM beta is not stable over time. We investigate the nature of the time-variation in betas using monthly Australian data from 1979 to 1994 for 23 sectors. We discuss beta estimates for sub-periods and tests of the statistical adequacy of the market model used to estimate the betas. We estimate time-varying betas using recursive regressions, rolling regressions and using the Kalman Filter. We find considerable time-variation in the estimated betas and find that many are non-stationary. We estimate a simple model which explains the variation in each of the betas in terms of a time trend, allowing for a break both in level and in trend at October 1987. The model explains a large proportion of the variation in the betas over the sample period for most of the sectors. (C) 1999 IMACS/Elsevier Science B.V. All rights reserved.

AB - It is well known that the CAPM beta is not stable over time. We investigate the nature of the time-variation in betas using monthly Australian data from 1979 to 1994 for 23 sectors. We discuss beta estimates for sub-periods and tests of the statistical adequacy of the market model used to estimate the betas. We estimate time-varying betas using recursive regressions, rolling regressions and using the Kalman Filter. We find considerable time-variation in the estimated betas and find that many are non-stationary. We estimate a simple model which explains the variation in each of the betas in terms of a time trend, allowing for a break both in level and in trend at October 1987. The model explains a large proportion of the variation in the betas over the sample period for most of the sectors. (C) 1999 IMACS/Elsevier Science B.V. All rights reserved.

U2 - 10.1016/S0378-4754(99)00033-6

DO - 10.1016/S0378-4754(99)00033-6

M3 - Article

VL - 48

SP - 531

EP - 539

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

SN - 0378-4754

ER -