A model to explicitly allow for risk in discounted cashflow analysis of investment property : A dissertation submitted in partial fulfilment of the requirements for the degree of Master of Property Studies at Lincoln University

Abstract

Property is a complex asset and is traded in a largely uninformed and imperfect market. Despite this, investors and their advisors are required to estimate the expected future returns of a property asset in order to determine its present day worth. These estimations carry the risk or uncertainty of the investment in that their accuracy will determine whether the estimation of present day worth is reasonable. Risk and uncertainty is defined in The Oxford Dictionary as follows: Risk 1 n. chance of injury or loss or bad consequence; person or thing causing risk. 2 v. t. expose to risk, venture on, take chances of. Uncertainty n. not certain; not to be depended on; changeable. In terms of allowing for risk and uncertainty in property investment, deterministic DCF analysis is generally viewed as an improvement on simple income capitalisation approaches. It allows for explicit future assumptions and thus risk. In addition, deterministic DCF analysis allows analysts to further explore risk typically by sensitivity and scenario analysis. However, given the current thinking on "most probable selling price" versus traditional deterministic investment value assessments and analysis, there is a growing requirement to explicitly allow for risk within a stochastic framework. In recognition that a valuation is an estimate of uncertain future events, valuation techniques should be governed by the concept of statistical probability as a means of simulating possible future occurrences. This paper explores the available options for considering risk in DCF analysis and sets out to develop a stochastic computer based model incorporating latest industry thinking for determining the most probable investment value or selling price.