Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/874
Title: Investment Risk Appraisal
Authors: Serguieva, A
Hunter, J
Keywords: fuzzy set theory, possibility theory, neural networks, investment project evaluation, capital asset pricing model
Issue Date: 2000
Publisher: Brunel University
Citation: Economics and Finance Working Papers, Brunel University, 00-15
Abstract: Standard financial techniques neglect extreme situations and regards large market shifts as too unlikely to matter. This approach may account for what occurs most of the time in the market, but the picture it presents does not reflect the reality, as the major events happen in the rest of the time and investors are ‘surprised’ by ‘unexpected’ market movements. An alternative fuzzy approach permits fluctuations well beyond the probability type of uncertainty and allows one to make fewer assumptions about the data distribution and market behaviour. Fuzzifying the present value criteria, we suggest a measure of the risk associated with each investment opportunity and estimate the project’s robustness towards market uncertainty. The procedure is applied to thirty-five UK companies and a neural network solution to the fuzzy criterion is provided to facilitate the decision-making process. Finally, we discuss the grounds for classical asset pricing model revision and argue that the demand for relaxed assumptions appeals for another approach to modelling the market environment.
URI: http://bura.brunel.ac.uk/handle/2438/874
Appears in Collections:Economics and Finance
Dept of Economics and Finance Research Papers

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