Biologically Inspired Algorithms for Financial Modelling - ReadingSample

1 Introduction Over the last decade, a considerable literature on biologically inspired algorithms (BIA) has emerged. These powerful algorithms can be used for prediction and classification, and have clear application for use in financial modelling and in the development of trading systems. Financial markets represent a complex, ever-changing, environment in which a population of investors are competing for profit. Biological entities have long inhabited such environments , and have competed for resources to ensure their survival. It is natural to turn to algorithms which are inspired by biological processes to tackle the task of survival in a financial jungle. The primary objectives of this book are twofold: to provide readers with an up-to-date introduction to a broad range of BIAs, and to illustrate by means of a series of case studies how the algorithms can be applied for the purposes of modelling financial markets, for the prediction of corporate failure, and for the prediction of credit ratings. Although we cannot provide any guarantees that these technologies provide an easy route to financial riches, we hope this book will spark new ideas in the minds of readers to encourage them to undertake their own work in the fascinating nexus of computer science and finance. This book is aimed at two audiences: those in the finance community who wish to learn about advances in biologically inspired computing and how these advances can be applied to financial modelling; and those in the computer science community who wish to gain insight into the domain of financial modelling and trading system design. Strong emphasis is placed in this book on evolutionary methodologies, particularly Grammatical Evolution [174]. This book is also suitable for use on advanced undergraduate or postgraduate courses, on quantitative finance or computational intelligence. No prior knowledge of either BIAs or financial prediction is assumed.