The primary goal of this book is to present to the scientific and management communities a selection of applications using more recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve the economics and financial problems. The selected examples could also serve as a starting point or as an opening out, in the SC and CWP techniques application to a wider range of problems in economics and finance.

Decision making in the present world is becoming more and more sophisticated, time consuming and difficult for human beings who require more and more computational support. This book addresses the significant increase on research and applications of Soft Computing and Computing with Words and Perceptions for decision making in Economics and Finance in recent years. Decision making is heavily based on information and knowledge usually extracted from the analysis of large amounts of data. Data mining techniques enabled with the capability to integrate human experience could be used for a more realistic business decision support. Computing with Words and Perceptions introduced by Lotfi Zadeh, can serve as a basis for such extension of traditional data mining and decision making systems. Fuzzy logic as a main constituent of CWP gives powerful tools for modeling and processing linguistic information defined on numerical domain.

Decision making techniques based on fuzzy logics in many cases have demonstrated better performance than competing approaches. The reason is that traditional, bivalent-logic-based approaches, are not a good fit to reality — the reality of pervasive imprecision, uncertainty and partiality of truth. On the other hand, traditional probabilistic interpretation of uncertainties in practice does not always correspond to the nature of uncertainties that often appear as the effects of subjective estimations. The list of practical situations, when it seems better to avoid the traditional probabilistic interpretation of uncertainty is very long. The centrepiece of fuzzy logic that everything is, or is allowed to be, a matter of degree, makes it possible to better deal with perception-based information. Such information plays an essential role in economics, finance and, more generally in all domains in which human perceptions and emotions are in evidence. For instance, it is the case for the studies of the capital markets/financial engineering including financial time series modeling; price projections for stocks, volatility analysis and the pricing of options and derivatives; and risk management to mention few.