Property market modelling and forecasting: simple vs complex models

Jadevicius, A and Huston, S (2015) Property market modelling and forecasting: simple vs complex models. Journal of Property Investment & Finance, 33 (4). pp. 337-361. ISSN 1463-578X

[img]
Preview
Text
JPIF-08-2014-0053-converted.pdf

Download (740kB) | Preview

Abstract

Purpose – The commercial property market is complex, but the literature suggests that simple models can forecast it. To confirm the claim, the purpose of this paper is to assess a set of models to forecast UK commercial property market. Design/methodology/approach – The employs five modelling techniques, including Autoregressive Integrated Moving Average (ARIMA), ARIMA with a vector of an explanatory variable(s) (ARIMAX), Simple Regression (SR), Multiple Regression, and Vector Autoregression (VAR) to model IPD UK All Property Rents Index. The Bank Rate, Construction Orders, Employment, Expenditure, FTSE AS Index, Gross Domestic Product (GDP), and Inflation are all explanatory variables selected for the research. Findings – The modelling results confirm that increased model complexity does not necessarily yield greater forecasting accuracy. The analysis shows that although the more complex VAR specification is amongst the best fitting models, its accuracy in producing out-of-sample forecasts is poorer than of some less complex specifications. The average Theil’s U-value for VAR model is around 0.65, which is higher than that of less complex SR with Expenditure (0.176) or ARIMAX (3,0,3) with GDP (0.31) as an explanatory variable models.

Item Type: Article
Keywords: United Kingdom, Market, Property, Modelling, Complex, Simple
Divisions: Real Estate and Land Management
Depositing User: Marieke Guy
Date Deposited: 15 Jan 2019 14:40
Last Modified: 22 May 2019 15:02
URI: http://rau.repository.guildhe.ac.uk/id/eprint/16100

Actions (login required)

Edit Item Edit Item