Generalised soft multi-mode real options model (fuzzy-stochastic approach)

Researchers and practitioners are dealing intensively with the real option valuation. One of the generalised types is reversible the multi-mode American real options. These options are solved mainly by applying the stochastic discrete binomial models. Uncertainty is a typical feature of valuation, and two basic types of representation are distinguished: risk (stochastic) and imprecision (fuzzy). The fuzzy-stochastic models indicate the generalised real options modelling containing both aspects. The objective of the paper is to develop and apply the generalised fuzzy-stochastic multi-mode real options model. This model is based on fuzzy numbers, the discrete binomial model, and the decomposition principle. Input data, particularly underlying cash-flows, are given by fuzzyrandom numbers; fuzzy numbers give terminal values, risk-free rate, switching cost. Furthermore, assumptions and computation procedures are also described. The proposed optimisation problem is used for the fuzzy multi-mode real option value calculation. Results are compared with sub-problems, crisp-stochastic multi-modes real options and partial fuzzy-stochastic multi-mode real options models. A stylised illustrative operational flexibility example of comparing the fuzzy-stochastic multi-mode real options models is presented and discussed. The model can serve to valuation, decision-making, generalised sensitivity analysis and control under a fuzzystochastic environment.Web of Science192art. no. 11638

The Structured Hedging of Financial Value: With Applications to Foreign Exchange Risk Management

The objective of the thesis is to develop a structured financial hedging framework that is empirically implementable and consistent with a corporate finance perspective. Value at risk provides a suitable framework for this purpose. The aversion implied in the value at risk and its generalised theory arises from a firm's concerns about contingent financial distress costs, which can be considered as the payoff of a put option written by stockholders of firms in favour of third parties. This enables the development of a hedging framework to explore how a firm's welfare might be enhanced by replacing natural exposures with hedged outcomes. An ideal hedging decision is to maximise the financial value in good times at minimal cost in terms of the generalised value at risk penalty function. In an efficient market, a fully hedged policy using forwards is generally the optimal decision, while alternatives should be taken into account where markets are not efficient. In such cases, the underlying empirical methodology should be able to detect inefficiencies and feed into the objective functions for maximising firm value. The empirical implementation is explored with a variety of econometric methodologies. These include the development of new semi-parametric or nonparametric techniques based upon wavelet analysis, as well as an incomplete forecasting algorithm. Such methods have been preferred to classical linear and stationary models, because they have broader application in an inefficient market where information is technically fuzzy and financial data may exhibit non-linearity or non-stationarity. Further decision dimensions concern exposure duration or path risk, in which individuals' perspectives of risk is time-dependent and linked to the evolution of value at risk through time. The proposed approaches find their main application in foreign exchange risk management, a topic of considerable importance and sensitivity in New Zealand. A statistically well-adapted hedge object for an exporter such as the dairy industry is the corporate terms of trade, which balances up output and expense prices as a single index related to the net profit margin. Further applications are to strategic fund management where the objective is to derive optimal foreign exchange forwards based hedges