Modelling and Forecasting Financial Data

Techniques of Nonlinear Dynamics

AvAbdol S. Soofi,Liangyue Cao

Inbunden, Engelska, 2002

Del i serien Studies in Computational Finance

3 273 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2002-03-31
Mått:155 x 235 x 29 mm
Vikt:928 g
Format:Inbunden
Språk:Engelska
Serie:Studies in Computational Finance
Antal sidor:488
Förlag:Kluwer Academic Publishers
ISBN:9780792376804

Utforska kategorier

Mikroekonomi inom Ekonomi och Ledarskap
Finansiering inom Ekonomi och Ledarskap

Recensioner i media

"This book is truly a multidisciplinary effort, with contributors including economists, electrical engineers, physicists, mathematicians, and statisticians (myself and Jianming Ye). 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)

Innehållsförteckning

I Embedding Theory: Time-Delay Phase Space Reconstruction and Detection of Nonlinear Dynamics.- 1 Embedding Theory: Introduction and Applications to Time Series Analysis.- 2 Determining Minimum Embedding Dimension.- 3 Mutual Information and Relevant Variables for Predictions.- II Methods of Nonlinear Modelling and Forecasting.- 4 State Space Local Linear Prediction.- 5 Local Polynomial Prediction and Volatility Estimation in Financial Time Series.- 6 Kalman Filtering of Time Series Data.- 7 Radial Basis Functions Networks.- 8 Nonlinear Prediction of Time Series Using Wavelet Network Method.- III Modelling and Predicting Multivariate and Input-Output Time Series.- 9 Nonlinear Modelling and Prediction of Multivariate Financial Time Series.- 10 Analysis of Economic Time Series Using NARMAX Polynomial Models.- 11 Modeling dynamical systems by Error Correction Neural Networks.- IV Problems in Modelling and Prediction.- 12 Surrogate Data Test on Time Series.- 13 Validation of Selected Global Models.- 14 Testing Stationarity in Time Series.- 15 Analysis of Economic Delayed-Feedback Dynamics.- 16 Global Modeling and Differential Embedding.- 17 Estimation of Rules Underlying Fluctuating Data.- 18 Nonlinear Noise Reduction.- 19 Optimal Model Size.- 20 Influence of Measured Time Series in the Reconstruction of Nonlinear Multivariable Dynamics.- V Applications in Economics and Finance.- 21 Nonlinear Forecasting of Noisy Financial Data.- 22 Canonical Variate Analysis and its Applications to Financial Data.