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

Marcel Aloy 1 Floris Laly 2 Sébastien Laurent 1, 3 Christelle Lecourt 1
1 AMSE - Aix-Marseille Sciences Economiques
2 Louvain School of Management (LFIN‐LIDAM, UCLouvain)
3 Aix-Marseille Graduate School of Management
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
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Submitted on : Friday, January 8, 2021 - 12:10:27 PM
Last modification on : Tuesday, October 19, 2021 - 10:50:28 PM

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Marcel Aloy, Floris Laly, Sébastien Laurent, Christelle Lecourt. Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs. 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⟩. ⟨hal-03103717⟩

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