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Bayesian Methods Applied To Reit Volatility Via Garch Models

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  • Colin Ward

Abstract

Volatility estimation is an integral component of risk management, option pricing, and portfolio allocation. REIT volatility is examined using a Bayesian GARCH model. This paper discusses shortfalls of maximum likelihood estimation, which are commonly used for estimating GARCH models, and elucidates the advantages of the Bayesian alternative. A portfolio allocation problem highlights the differences in decision making from these methods. Conditional variance estimation uncertainty is found to increase with volatility.

Suggested Citation

  • Colin Ward, 2008. "Bayesian Methods Applied To Reit Volatility Via Garch Models," ERES eres2008_288, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2008_288
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    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2008-288
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    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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