Modelling and Forecasting Financial Data

1. Problems in Modelling and Prediction

   1. Analysis of Economic Delayed-Feedback Dynamics

      • Henning U. Voss, Jürgen Kurths

      Pages 327-349

   2. Global Modeling and Differential Embedding

      • J. Maquet, C. Letellier, G. Gouesbet

      Pages 351-374

   3. Estimation of Deterministic and Stochastic Rules Underlying Fluctuating Data

      • S. Siegert, R. Friedrich, Ch. Renner, J. Peinke

      Pages 375-399

   4. Nonlinear Noise Reduction

      • Rainer Hegger, Holger Kantz, Thomas Schreiber

      Pages 401-416

   5. Optimal Model Size

      • Jianming Ye

      Pages 417-428

   6. Influence of Measured Time Series in the Reconstruction of Nonlinear Multivariable Dynamics

      • C. Letellier, L. A. Aguirre

      Pages 429-451

2. Applications in Economics and Finance

   1. Front Matter

      Pages 453-453

      PDF

   2. Nonlinear Forecasting of Noisy Financial Data

      • Abdol S. Soofi, Liangyue Cao

      Pages 455-465

   3. Canonical Variate Analysis and Its Applications to Financial Data

      • Berndt Pilgram, Peter Verhoeven, Alistair Mees, Michael McAleer

      Pages 467-481

3. Back Matter

   Pages 483-488

   PDF

Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contributors to this volume have agreed to make available to readers upon request all computer programs used to implement the methods discussed in their respective chapters.
Modelling and Forecasting Financial Data is a valuable resource for researchers and graduate students studying complex systems in finance, biology, and physics, as well as those applying such methods to nonlinear time series analysis and signal processing.

• Finance
• calculus
• complex systems
• data analysis
• dynamical systems
• dynamics
• economics
• forecasting
• modeling
• nonlinear dynamics
• time series
• time series analysis
• volatility

"This book is truly a multidisciplinary effort, with contributors including economists, electrical engineers, physicists, mathematicians, and statisticians (myself and Jianming Yé). Although there are many books on nonlinear dynamic techniques, Modelling and Forecasting Financial Data is distinguished by its concerted efforts on practical relevance in financial and economic applications."
(Z.-Q. John Lu, National Institute of Standards and Technology in Technometrics, 46:1 (February 2004)

• Department of Economics, University of Wisconsin-Platteville, USA

  Abdol S. Soofi

• Department of Mathematics, University of Western Australia, Australia

  Liangyue Cao

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