Fuzzy Parameters for Evaluating Capital Investments

In the process of doing capital budgeting, one of the required steps is to evaluate the investment value of the candidates, while the net present value (NPV) is always a trustworthy indicator. This work presents a series of pragmatic algorithms for calculating the return and risk parameters of NPV in fuzzy numbers, which are anticipated to do a better job in an uncertain environment than traditional crisp-number equations due to their effectiveness in capturing the abstract qualitative information as well as the quantitative information. These algorithms cope with the randomness of outcomes and the vagueness of data estimation and can efficiently integrate the information. The return parameters (EFNPVs) include the expected fuzzy NPV, the equivalent annuity, and the equivalent annuity to infinity. The risk parameter goes to the fuzzy lower partial moment (FLPM), which measures the absolute value of the expected below-target loss in terms of a capitalist's risk tolerance and is more realistic than the commonly used standard deviation. A performance ratio is further defined as the expected excess-target return to LPM. The candidate with a high EFNPV, a low FLPM, and/or a high performance ratio is a priority.