Modelling and Forecasting Financial Data: Techniques of Nonlinear Dynamics

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The contributors to this volume assert that dynamical systems theory and related nonlinear methods have had a major impact on the analysis of time series data from complex systems. Contemporary developments in mathematical methods of state-space reconstruction, time-delay embedding and surrogate data analysis, coupled with readily accessible and powerful computational facilities used in gathering and processing massive quantities of high-frequency data, have provided theorists and practitioners with opportunities for exploratory data analysis, modelling, forecasting and control. This book brings together an accessible set of chapters that deal with the application of nonlinear dynamics and associated algorithms to the study of economies and markets as complex systems. To make such methods readily useful in practice, the contributors have agreed to make available to readers upon request all computer programs used to implement the methods discussed in their respective chapters.