The present study analyzes the extra insights that option pricing models may achieve when uncertainty about parameters is modeled through fuzzy numbers. Specifically, the authors consider the Heston stochastic volatility model, which assumes that stock price changes and their instantaneous...

In this paper we study the tail behaviour of eight major market indexes stratifying data according to the violation of a high threshold on the previous day. The distributional differences found can be exploited to improve VaR calculations in several settings, giving rise to what we call 'MCVaR'....

This paper adopts a promising concept of uncertainty, incorporating both stochastic processes and fuzzy theory to capture the somewhat vague and imprecise ideas the manager has about the future expected cash flows, the profitability of the project, the costs of the project and many other...

The fuzzy transform (F-transform), introduced by I. Perfilieva, is a powerful tool for the construction of fuzzy approximation models; it is based on generalized fuzzy partitions and it is obtained by minimizing a quadratic (L₂-norm) functional. In this paper we describe an analogous...

In this paper we introduce uncertainty in the investment appraisal, managed through a new criterion called Average Internal Rate of Return (AIRR), introduced in Magni (2010). The consistency of the arithmetic of variables represented with intervals or fuzzy numbers makes it possible to apply the...

In investment appraisal, uncertainty can be managed through intervals or fuzzy numbers because the arithmetical properties and the extension principle are well established and can be successfully applied in a rigorous way. We apply interval and fuzzy numbers to the Average Internal Rate of...