A Fuzzy Discounted Cash Flow Analysis for Real Estate Investment
In a discounted cash flow (DCF) analysis, reliability and credibility of results are strictly dependent on the prediction of key input variables. There are two approaches at which these inputs can be rigorously determined. The first approach involves the use of standard statistical tools such as the multiple regression analysis and the Box-Jenkin’s time series models. These tools are not foolproof and are fettered by inherent statistical weaknesses. Based on probabilistic assumptions, results of the statistical analysis are bounded by occurrences of ex-post random events or observations. In a complex world, randomness alone is insufficient to capture dynamics and changes in real world events. Ex-ante expert judgement of events in a near future,1 which does not rely on probabilities of ex-post events or information, offers an alternative way to arrive at a prediction of the input variables.
KeywordsIncome Expense Peri
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- Gupta, M. M. “Fuzzy-ism”, The First Decade, in M. M. Gupta, G. N. Saridis and B. R. Gaines, editors, Fuzzy Automata and Decision Processes, Elsevier Notrth-Holland, 1977, 5–10.Google Scholar
- Klir, G. F. and Folger, T. A. Fuzzy Sets, Uncertainty and Information, Prentice Hall, International Edition, 1992.Google Scholar
- Makridakis, S. and Wheelwright, S. C. editors, Forecasting the future and the future of forecasting, in Managerial Sciences: Vol 12, Forecasting, Amsterdam: North Holland, 1979.Google Scholar
- Reynolds, T. J., Kent L. E., and Lazenby, D. W. Introduction to Structural Mechanics, London: Hodder and Stoughton, 1977.Google Scholar
- von Winterfeldt, D. and Edward, W. Decision Analysis and Behavioural Research, New York, Cambridge University Press, 1986.Google Scholar
- Zadeh, L. A. Fuzzy Set Theory — A Perspective, in M. M. Gupta, G. N. Saridis and B. R. Gaines, editors, Fuzzy Automata and Decision Processes, Elsevier North-Holland, 1977, 3–4Google Scholar