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Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs

  • Marcel Aloy
  • Floris Laly
  • Sébastien LaurentEmail author
  • Christelle Lecourt
Chapter
  • 13 Downloads
Part of the Dynamic Modeling and Econometrics in Economics and Finance book series (DMEF, volume 27)

Abstract

Beta coefficients are the cornerstone of asset pricing theory in the CAPM and multiple factor models. This chapter proposes a review of different time series models used to estimate static and time-varying betas, and a comparison on real data. The analysis is performed on the USA and developed Europe REIT markets over the period 2009–2019 via a two-factor model. We evaluate the performance of the different techniques in terms of in-sample estimates as well as through an out-of-sample tracking exercise. Results show that dynamic models clearly outperform static models and that both the state space and autoregressive conditional beta models outperform the other methods.

Keywords

Real estate REITs Multivariate GARCH State space Dynamic conditional beta Autoregressive conditional beta 

JEL Classification

C13 C32 C40 C53 C58 G12 R33 

Notes

Acknowledgements

The second author gratefully thanks the FNRS for financial support.

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Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Marcel Aloy
    • 1
  • Floris Laly
    • 2
  • Sébastien Laurent
    • 1
    • 3
    Email author
  • Christelle Lecourt
    • 1
  1. 1.Aix-Marseille University (Aix-Marseille School of Economics), CNRS & EHESSMarseilleFrance
  2. 2.UCLouvain (Louvain School of Management), LFIN-LIDAMLouvain-la-NeuveBelgium
  3. 3.Aix-Marseille Graduate School of Management – IAEAix-en-ProvenceFrance

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