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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Floris Laly: UCLouvain (Louvain School of Management), LFIN-LIDAM

A chapter in Recent Econometric Techniques for Macroeconomic and Financial Data, 2021, pp 229-264 from Springer

Abstract: 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)
JEL-codes: C13 C32 C40 C53 C58 G12 R33 (search for similar items in EconPapers)
Date: 2021
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Working Paper: 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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DOI: 10.1007/978-3-030-54252-8_9

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