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

Marcel Aloy, Floris Laly, Sébastien Laurent and Christelle Lecourt

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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 (search for similar items in EconPapers)
Date: 2021-01
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Published in Gilles Dufrénot; Takashi Matsuki. Recent Econometric Techniques for Macroeconomic and Financial Data, Springer International Publishing, pp.229-264, 2021, Dynamic Modeling and Econometrics in Economics and Finance, 978-3-030-54252-8. ⟨10.1007/978-3-030-54252-8_9⟩

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Chapter: Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs (2021)
Working Paper: Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03103717

DOI: 10.1007/978-3-030-54252-8_9

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