Evolutionary Computation for Modelling and Optimization in Finance

In the last decades, there has been a tendency to move away frommathematically tractable, but simplistic models towards more sophisticated andreal-world applicable models in nance. However, the consequence of the improvedsophistication is that the model specication and analysis is no longer mathematically tractable. Instead solutions need to be numerically approximated. For thistask, evolutionary computation heuristics are the appropriate means, because theydo not require any rigid mathematical properties of the model, such as linearityor convexity. Evolutionary algorithms are search heuristics, usually ispired by Darwinian evolution and Mendelian inheritance, which aim to determine the optimalsolution to a given problem by competition and alteration of candidate solutions ofa population. In this work, we focus on credit risk modelling and nancial portfoliooptimization to point out how evolutionary algorithms can easily provide realiableand accurate solutions to challenging financial problems.