BAYESIAN METHODS APPLIED TO REIT VOLATILITY VIA GARCH MODELS
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.
Year of publication: |
2008
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Authors: | Ward, Colin |
Institutions: | European Real Estate Society - ERES |
Saved in:
freely available
Extent: | text/html |
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Series: | ERES. |
Type of publication: | Book / Working Paper |
Source: |
Persistent link: https://www.econbiz.de/10010799393
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