Enhancing information use to improve predictive performance in property markets

Patrick J. Wilson (School of Finance and Economics, University of Technology, Sydney and Visiting Scholar,University of Wollongong, Gwynneville, Australia, and)
John Okunev (School of Banking and Finance, University of New South Wales, Sydney, Australia)

Journal of Property Investment & Finance

ISSN: 1463-578X

Publication date: 1 December 2001

Abstract

Over the last decade or so there has been an increased interest in combining the forecasts from different models. Pooling the forecast outcomes from different models has been shown to improve out‐of‐sample forecast test statistics beyond any of the individual component techniques. The discussion and practice of forecast combination has revolved around the pooling of results from individual forecasting methodologies. A different approach to forecast combination is followed in this paper. A method is used in which negatively correlated forecasts are combined to see if this offers improved out‐of‐sample forecasting performance in property markets. This is compared with the outcome from both the original model and with benchmark naïve forecasts over three 12‐month out‐of‐sample periods. The study will look at securitised property in three international property markets – the USA, the UK and Australia.

Keywords

Citation

Wilson, P.J. and Okunev, J. (2001), "Enhancing information use to improve predictive performance in property markets", Journal of Property Investment & Finance, Vol. 19 No. 6, pp. 472-497. https://doi.org/10.1108/14635780110406851

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Publisher

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MCB UP Ltd

Copyright © 2001, MCB UP Limited

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