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Development of a Sesma model for short-term investment decision-making.

Jadevicius, Arvydas; Sloan, Brian; Brown, Andrew


Arvydas Jadevicius

Brian Sloan


ARIMA models have been extensively used for property market modelling. Property researchers have used this type of univariate forecasting technique to predict property rents, returns and yields. However, it has been indicated that ARIMA models could be improved. Accordingly, this current research examines an alternative specification of the ARIMA technique. The proposed model replaces the Autoregressive (AR) element with Simple Exponential Smoothing (SES) element within the ARIMA framework. This creates a SESMA model. The empirical results indicate that this mathematical manipulation improves model out-of-sample forecasting accuracy. This therefore suggests that the SESMA model could successfully be employed for short-term investment decision-making.

Conference Name 4th Annual Conference of the Global Chinese Real Estate Congress (GCREC)
Start Date Jul 3, 2012
End Date Jul 5, 2012
Publication Date Mar 7, 2012
Deposit Date Mar 9, 2012
Publicly Available Date Mar 9, 2012
Peer Reviewed Not Peer Reviewed
Pages 1195
ISBN 978-7-5642-1401-2
Keywords Commercial property; exponential smoothing; modelling; UK;
Public URL


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