A fuzzy real option approach for investment project valuation

[[abstract]]The main purpose of this paper is to propose a fuzzy approach for investment project valuation in uncertain environments from the aspect of real options. The traditional approaches to project valuation are based on discounted cash flows (DCF) analysis which provides measures like net present value (NPV) and internal rate of return (IRR). However, DCF-based approaches exhibit two major pitfalls. One is that DCF parameters such as cash flows cannot be estimated precisely in the uncertain decision making environments. The other one is that the values of managerial flexibilities in investment projects cannot be exactly revealed through DCF analysis. Both of them would entail improper results on strategic investment projects valuation. Therefore, this paper proposes a fuzzy binomial approach that can be used in project valuation under uncertainty. The proposed approach also reveals the value of flexibilities embedded in the project. Furthermore, this paper provides a method to compute the mean value of a project’s fuzzy expanded NPV that represents the entire value of project. Finally, we use the approach to practically evaluate a project.[[incitationindex]]SCI[[booktype]]紙

Fuzzy Optimization of Option Pricing Model and Its Application in Land Expropriation

Option pricing is irreversible, fuzzy, and flexible. The fuzzy measure which is used for real option pricing is a useful supplement to the traditional real option pricing method. Based on the review of the concepts of the mean and variance of trapezoidal fuzzy number and the combination with the Carlsson-Fuller model, the trapezoidal fuzzy variable can be used to represent the current price of land expropriation and the sale price of land on the option day. Fuzzy Black-Scholes option pricing model can be constructed under fuzzy environment and problems also can be solved and discussed through numerical examples

Pricing Currency Option Based on the Extension Principle and Defuzzification via Weighting Parameter Identification

We present a fuzzy version of the Garman-Kohlhagen (FG-K) formula for pricing European currency option based on the extension principle. In order to keep consistent with the real market, we assume that the interest rate, the spot exchange rate, and the volatility are fuzzy numbers in the FG-K formula. The conditions of a basic proposition about the fuzzy-valued functions of fuzzy subsets are modified. Based on the modified conditions and the extension principle, we prove that the fuzzy price obtained from the FG-K formula for European currency option is a fuzzy number. To simplify the trade, the weighted possibilistic mean (WPM) value with a weighting function is adopted to defuzzify the fuzzy price to a crisp price. The numerical example shows our method makes the α-level set of fuzzy price smaller, which decreases the fuzziness. The example also indicates that the WPM value has different approximation effects to real market price by taking different values of weighting parameter in the weighting function. Inspired by this example, we provide a method, which can identify the optimal parameter

Pricing currency options based on fuzzy techniques

Owing to the fluctuation of financial markets from time to time, some financial variables can always be observed with perturbations and be expected in the imprecise sense. Therefore, this paper starts from the fuzzy environments of currency options markets, introduces fuzzy techniques, and gives a fuzzy currency options pricing model. By turning exchange rate, interest rates and volatility into triangular fuzzy numbers, the currency option price will turn into a fuzzy number. This makes the financial investors who can pick any currency option price with an acceptable belief degree for their later use. In order to obtain the belief degree, an optimization procedure has been applied. An empirical study is performed based on daily foreign exchange market data. The empirical study results indicate that the fuzzy currency options pricing method is a useful tool for modeling the imprecise problem in the real world.Finance Pricing Fuzzy sets Currency options

Pricing Brazilian Exchange Rate Options Using An Adaptive Network-based Fuzzy Inference System

Recently, option pricing has become the focus of risk managers, policymakers, traders and more generally all market participants, since they find valuable information in these contracts. This paper suggests the pricing performance evaluation on Brazilian exchange rate R$(Reais) per US$ (U.S. Dollar) option contracts, traded at the Brazilian derivatives market, using an adaptive networkbased fuzzy inference system, for the period from April 1999 to April 2009. A fuzzy rule-based system was built with a family of conditional if-then statements whose consequent are functions of the antecedents, and then composed with the aid of fuzzy neurons. The ANFIS model was compared against the Black closedform formula and some neural networks topologies, considering traditional error measures and statistical tests. 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