An Overview of the Forecasting Methods Used in Real Estate Housing Price Modelling
DOI:
https://doi.org/10.11113/jt.v73.4337Keywords:
Forecasting methods, forecasting errors, real estate modellingAbstract
Forecasting is very fundamental in real estate where the past transactions become the evidences while decision making for the present and the future. Several techniques and validation approached that were commonly used in housing price index forecasting. Beside the appropriate forecasting method, error calculation is one of the critical constraints in accuracy out of all methods. This paper overview the available methods and the types of error being considered in forecasting techniques. Then the forecasting methods, namely Multiple Regression Analysis (MRA) and Artificial Neural Network which are highly applied in forecasting modelling are compared over its error accuracy. Â
References
Alho, J. M. 1990. Stochastic Methods in Population Forecasting. International Journal of Forecasting. 6(4): 521–530.
Armstrong, J. S. 2001. Principles of Forecasting. A Handbook for Researchers and Practioners. Springer 2001. ISBN: 0-7923-7930-6.
Barr, G. D. I, Sparks, R., Affleck Graves, J., & Thompson, M. L. 1996. Selection Criteria for Regression Models and Their Application to Abnormal Event Studies in Finance. South African Statistical Journal. 30(2): 155–173.
Chaplin, R. 2000. Predicting Real Estate Rents: Walking Backwards into the Future. Journal of Property Investment and Finance. 18: 352–370.
Cegielski, C., Kitchens, F., Rebman, C., & Lang, T. 2002. What is a Dot-Com Worth? An Exploration of the Value Estimates of Information Technology-based Firms. Journal of Computer Information Systems. 43(2): 31–35.
Cheng, L. T. W., Fung, J. K. W., & Chan, K. C. 2000. Pricing Dynamics of Index Options and Index Futures in Hong Kong Before and During the Asian Financial Crisis. Journal of Futures Markets. 20(2): 145–166.
Epstein, J. M., Axtell, R. 1996. 2050 Project. Growing Artifcial Societies: Social Science from the Bottom Up. Washington, D.C.: Brookings Institution Press.
Fox, J., & Fox, J. 2008. Applied Regression Analysis and Generalized Linear Models. 2nd Ed. Los Angeles: Sage.
Gardner, E. S. 1985. Exponential Smoothing: the State of the Art. Journal of Forecasting. 4(1): 1–28.
Garrick S., & Raymond. W. 2001. The Validity of Forecasting. Pacific Rim Real Estate Society International Conference Christchurch.
Gilbert, G. N. 2008. Agent-Based Models. Los Angeles: Sage Publications.
Gurney, K. 1997. An Introduction to Neural Networks. London: Routledge. ISBN 1-85728-673-1.
Hasan Selim. 2009. Determinants of House Prices in Trukey: Hedonic Regression Versus Artificial Neural Network. Journal of Expert Systems with Applications. 36(2). ISBN: 2843-2852.
Heather B., & Leonie T. 2008. Mortality Modelling and Forecasting: A Review of Methods. The Australian Demographic & Social Research Institute Working Papers. Official url : http://adsri.anu.edu.au [Accessed June 2013].
Theil, H., Raj, B., & Koerts, J. 1992. Henri Theil’s Contributions to Economics and Econometrics: Econometric Theory and Methodology. Publisher: Springer Science & Business Media. ISBN 0-7923-1548-0.
Hua, G. B. 1997. An Evaluation of the Accuracy of the Multiple Regression Approach in Forecasting Sectoral Construction Demand in Singapore. Construction Management. 17(2): 231–241.
Julio Gallego, M. E. 2004. Artificial Intelligence Applied to Real Estate Valuation: An Example for the Appriasal of Madrid. JULIO GALLEGO MORA –ESPERANZA. 255–265.
Keilman, N. 1990. Uncertainty in Population Forecasting Analyses, Recommendations. Swets & Zeitlinger, Amsterdam.
KOREAN PUBLIC ADMINISTRATION REVIEW. 2003. Alternatives for Improving the Indexes for Building Assessment in Property Tax. Publisher: The Korean Association for Public Administration. ISSN: 1226-2536. 37(3): 263–289.
Lawrence, M., Goodwin, P., O’Connor, M., & Onkal, D. 2006. Judgemental Forecasting: A Review of Progress Over the Last 25 Years. International Journal of Forecasting. 22: 493–518.
Lapide, L. 2008. Thinking About Composite Forecasting. The Journal of Business Forecasting. 27(2).
Makridakis, S. G., Wheelwright, S. C., & Hyndman, R. J. 1998. Forecasting: Methods and Applications. 3rd ed. New York: John Wiley & Sons.
Mark, J., & Goldberg, M. 1998. Multiple Regression Analysis and Market Assessment: A Review of the Issues. Appraisal Journal. 56(1): 89–109.
Miller, J. H., & Page, S. E. 2007. Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton, N.J.: Princeton University Press.
Mitchell, P.and McNamara, P. 1997. Issues in the Development and Application of Property Market Forecasting: The Investor’s Perspective. Journal of Property Finance. 8: 363–376.
Mohamad, S. M. R., Chitrakala, M., Norhaya, K., & Izran, S. 2012. Forecasting Housing Price Index Using Artificial Neural Network Technique. Malaysian Journal of Real Estate. 7(1). ISBN: 1832-8505.
Montgomery, D. C., Jennings, C. L., & Kulahci, M. 2008. Introduction to Time Series Analysis and Forecasting. Hoboken, N.J.: 34.: Wiley-Interscience.
Ng, S. T., M. Skitmore, et al. 2008. Using Genetic Algorithms and Linear Regression Analysis for Private Housing Demand Forecast. Building and Environment. 43(6): 1171–1184.
Nguyen, N. and A. Cripps. 2001. Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks. Journal of Real Estate Research. 22(3): 313–336.
Peter, O., & Eriki, R. I. U. 2008. Application of Neural Network in Evaluating Price of Housing Units in Nigeria: A Preliminary Investigation. Journal of Artificial Inteligence.
Peter Rossini. 1997. Application of Artificial Neural Networks to the Valuation of Residential Property. Proceedings from the 3rd annaul pacific-Rim Real Estate Society Conference, New Zealand, Jan. 1997.
Shapiro, A. F., Pfumm, J. S., & DeFilippo, T. A. 1999. The Inner Workings of Neural Networks and Genetic Algorithms. Actuarial Research Clearing House. 1: 415–426.
Seow E. O., Teck. I. C. 1996. Singapore Residential Market: An Expert Judgemental Forecast Incorporating the Analytical Hierarchy Process. Journal of Property Valuation and Investment. 14.
Stanley McGreal, A. A., Dylan McBurney, David Patterson. 1998. Neural Networks: The Prediction of Residential Values. Journal of Property Valuation and Investment. 16(1): 57–70.
Xiaoli Yang, & Qiong He. 2013. Influence of Modeling Methods for Housing Price Forecasting. Advanced Materials Research. 798–799: 885–888.
West, M., & Harrison, J. 1997. Bayesian Forecasting and Dynamic Models. 2nd edition. Publisher: Springer, New York.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
