This paper discusses the problem of capital budgeting in the situation where only some model parameters are well described by their past data and therefore are specified by random variables, whereas the remaining model parameters can hardly be predicted by historical data and therefore they are described by means of fuzzy variables. In order to be able to process such hybrid data, a model of th...

This paper provides a new approach for valuing a wide set of capital budgeting problems with many embedded real options dependent on many state variables and a related valuation algorithm based on Monte Carlo simulation. The valuation approach decomposes of a complex real option problem with many options into a set of simple options, but taking into account deviations from value additivity due ...

This paper provides a valuation algorithm based on Monte Carlo simulation for valuing a wide set of capital budgeting problems with many embedded real options dependent on many state variables. Along the lines of Gamba and Trigeorgis (2002b), we decompose a complex real option problem with many options into a set of simple options, properly taking into account deviations from value additivity d...

This paper deals with R&D priority setting. It advocates for the introduction of strategic capital budgeting methodologies that will unite the hitherto largely independent processes of strategic planning and capital budgeting. Significant advances in economics and finance theory regarding valuing derivative securities, such as futures and options, and in computing power over the past twenty yea...

In this paper the impact of product market uncertainty on the optimal replacement timing of a production facility is studied. The existing production facility can be replaced by a technologically more advanced and thus more cost-effective one. We take into account strategic interactions among the firms competing in the product market by analyzing the problem in a duopolistic setting. We calcula...