BAYESIAN METHODS APPLIED TO REIT VOLATILITY VIA GARCH MODELS

Colin Ward

ERES from European Real Estate Society (ERES)

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.

JEL-codes: R3 (search for similar items in EconPapers)
Date: 2008-01-01
References: Add references at CitEc
Citations:

Downloads: (external link)
https://eres.architexturez.net/doc/oai-eres-id-eres2008-288 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arz:wpaper:eres2008_288

Access Statistics for this paper

More papers in ERES from European Real Estate Society (ERES) Contact information at EDIRC.
Bibliographic data for series maintained by Architexturez Imprints ().