Forecasting future trends in Dubai housing market by using Box‐Jenkins autoregressive integrated moving average

Abstract

Purpose -It is important to forecast index series to identify future rises, falls, and turning points in the property market. From the point of this necessity and importance, the main purpose of this paper is to forecast the future trends in Dubai housing market. Design/methodology/approach -This paper uses the monthly time series of Reidin.com Dubai Residential Property Price Index (DRPPI) data. In order to forecast the future trends in Dubai housing market, Box-Jenkins autoregressive integrated moving average (ARIMA) forecasting method is utilized. Findings -The results of the ARIMA modeling clearly indicate that average monthly percentage increase in the Reidin.com DRPPI will be 0.23 percent during the period January 2011-December 2011. That is a 2.44 percent increase in the index for the same period. Practical implications -Reidin.com residential property price index is a crucial tool to measure Dubai's real estate market. Based on the current index values or past trend, real estate investors (i.e. developers and constructors) decide to start new projects. Attempts have also been made in the past to forecast index series to identify future rises, falls, and turning points in the property market. The results of this paper would also help government and property investors for creating more effective property management strategies in Dubai. Originality/value -There is no previous study analyzing the future trends in Dubai housing market. At this point, the paper is the first academic study that identifies this relationship.

Forecasting Property Price Indices in Hong Kong Based on Grey Models

“…The property price forecasting has been studied by many researchers. Existing studies show that there are many types of classification of the forecasting methods, including multivariate models and univariate models (Hepsen, Vatansever 2011), complex models and simple models (Jadevicius et al 2013), traditional models and advanced models (Pagourtzi et al 2003), statistical models and artificial intelligence models (Kayacan et al 2010), etc. Several studies have been focused on the comparison among different methods.…”

“…ARIMA models have frequently been used in forecasting the real estate market. For example, the models have been applied in forecasting the real estate market of Hong Kong and Dubai (Hepsen, Vatansever 2011;Tse 1997). There are different models in the ARIMA family, including ARIMAX and ARIMAX-GARCH.…”

The Impact Of Macroeconomic Variables On Real Estate Price Forecasting Modelling In Abuja Nigeria

“…Furthermore, [22] forecasted the potential movement of Dubai real estate price through Box-Jenkins technique with the monthly values of real estate index. The result affirmed that ARIMA is the appropriate model that described the data better.…”

Does proximity to tourist site affect the rental value of residential properties? Empirical evidence from Nigeria

“…These shreds of evidence found in the literature show that the residential property market is an important segment of any economy. In the existing literature, the predictive models for this class of properties focused on countries such as Australia [4]; Dubai [5]; Hong Kong [6]; New Zealand [7]; Nigeria [8]; United Kingdom [9] and United States of America [10], among others.…”