Nonlinear Time Series: Analysis with Applications to Foreign Exchange Rate Volatility

Nonlinear Time Series: Analysis with Applications to Foreign Exchange Rate Volatility PDF Author: Christian M. Hafner
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description

Nonlinear Time Series: Analysis with Applications to Foreign Exchange Rate Volatility

Nonlinear Time Series: Analysis with Applications to Foreign Exchange Rate Volatility PDF Author: Christian M. Hafner
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


Nonlinear Time Series Analysis with Applications to Foreign Exchange Rate Volatility

Nonlinear Time Series Analysis with Applications to Foreign Exchange Rate Volatility PDF Author: Christian Hafner
Publisher: Springer Science & Business Media
ISBN: 3662126052
Category : Business & Economics
Languages : en
Pages : 235

Get Book Here

Book Description
The book deals with the econometric analysis of high frequency financial time series. It emphasizes a new nonparametric approach to volatility models and provides theoretical and empirical comparisons with conventional ARCH models, applied to foreign exchange rates. Nonparametric models are discussed that cope with asymmetry and long memory of volatility as well as heterogeneity of higher conditional moments.

Non-Linear Time Series Models in Empirical Finance

Non-Linear Time Series Models in Empirical Finance PDF Author: Philip Hans Franses
Publisher: Cambridge University Press
ISBN: 0521770416
Category : Business & Economics
Languages : en
Pages : 299

Get Book Here

Book Description
This 2000 volume reviews non-linear time series models, and their applications to financial markets.

Nonlinear Time Series Analysis of Economic and Financial Data

Nonlinear Time Series Analysis of Economic and Financial Data PDF Author: Philip Rothman
Publisher: Springer Science & Business Media
ISBN: 1461551293
Category : Business & Economics
Languages : en
Pages : 379

Get Book Here

Book Description
Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.

Macroeconometrics and Time Series Analysis

Macroeconometrics and Time Series Analysis PDF Author: Steven Durlauf
Publisher: Springer
ISBN: 0230280838
Category : Business & Economics
Languages : en
Pages : 417

Get Book Here

Book Description
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.

Nonlinear Time Series Analysis

Nonlinear Time Series Analysis PDF Author: Holger Kantz
Publisher: Cambridge University Press
ISBN: 1139440438
Category : Science
Languages : en
Pages : 390

Get Book Here

Book Description
The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.

Nonlinear Time Series Analysis

Nonlinear Time Series Analysis PDF Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1119264073
Category : Mathematics
Languages : en
Pages : 466

Get Book Here

Book Description
A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.

Studies on Economics Sciences

Studies on Economics Sciences PDF Author: Yuksel Akay Unvan
Publisher: Livre de Lyon
ISBN: 2382360720
Category : Business & Economics
Languages : en
Pages : 100

Get Book Here

Book Description
Studies on Economics Sciences

Applied Informatics

Applied Informatics PDF Author: Hector Florez
Publisher: Springer Nature
ISBN: 3030896544
Category : Computers
Languages : en
Pages : 512

Get Book Here

Book Description
This book constitutes the thoroughly refereed papers of the 4th International Conference on Applied Informatics, ICAI 2021, held in Buenos Aires, Argentina, in October, 2021.The 35 full papers were carefully reviewed and selected from 89 submissions. The papers are organized in topical sections on artificial intelligence; data analysis; decision systems; health care information systems; image processing; security services; simulation and emulation; smart cities; software and systems modeling; software design engineering.

Modelling and Forecasting Financial Data

Modelling and Forecasting Financial Data PDF Author: Abdol S. Soofi
Publisher: Springer Science & Business Media
ISBN: 9780792376804
Category : Business & Economics
Languages : en
Pages : 528

Get Book Here

Book Description
Over the last decade, dynamical systems theory and related nonlinear methods have had a major impact on the analysis of time series data from complex systems. Recent 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 unparalleled opportunities for exploratory data analysis, modelling, forecasting, and control. Until now, research exploring the application of nonlinear dynamics and associated algorithms to the study of economies and markets as complex systems is sparse and fragmentary at best. 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.