Threshold autoregressive and Markov switching models: an application to commercial real estateMaitland-Smith, J. K. and Brooks, C. ORCID: https://orcid.org/0000-0002-2668-1153 (1999) Threshold autoregressive and Markov switching models: an application to commercial real estate. Journal of Property Research, 16 (1). pp. 1-19. ISSN 1466-4453 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1080/095999199368238 Abstract/SummaryAlthough financial theory rests heavily upon the assumption that asset returns are normally distributed, value indices of commercial real estate display significant departures from normality. In this paper, we apply and compare the properties of two recently proposed regime switching models for value indices of commercial real estate in the US and the UK, both of which relax the assumption that observations are drawn from a single distribution with constant mean and variance. Statistical tests of the models' specification indicate that the Markov switching model is better able to capture the non-stationary features of the data than the threshold autoregressive model, although both represent superior descriptions of the data than the models that allow for only one state. Our results have several implications for theoretical models and empirical research in finance.
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