Non Linear Time Series Models In Empirical Finance
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Non Linear Time Series Models In Empirical Finance
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Author : Philip Hans Franses
language : en
Publisher: Cambridge University Press
Release Date : 2000-07-27
Non Linear Time Series Models In Empirical Finance written by Philip Hans Franses and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-07-27 with Business & Economics categories.
This 2000 volume reviews non-linear time series models, and their applications to financial markets.
Non Linear Time Series Models In Empirical Finance
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Author : Philip Hans Franses
language : en
Publisher:
Release Date : 2000
Non Linear Time Series Models In Empirical Finance written by Philip Hans Franses and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Non Linear Time Series Models In Empirical Finance
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Author : Philip Hans Franses
language : en
Publisher:
Release Date : 2000
Non Linear Time Series Models In Empirical Finance written by Philip Hans Franses and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Nonlinear Time Series Analysis Of Economic And Financial Data
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Author : Philip Rothman
language : en
Publisher: Springer Science & Business Media
Release Date : 1999-01-31
Nonlinear Time Series Analysis Of Economic And Financial Data written by Philip Rothman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-01-31 with Business & Economics categories.
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.
Time Series Models For Business And Economic Forecasting
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Author : Philip Hans Franses
language : en
Publisher: Cambridge University Press
Release Date : 1998-10-15
Time Series Models For Business And Economic Forecasting written by Philip Hans Franses and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-15 with Business & Economics categories.
The econometric analysis of economic and business time series is a major field of research and application. The last few decades have witnessed an increasing interest in both theoretical and empirical developments in constructing time series models and in their important application in forecasting. In Time Series Models for Business and Economic Forecasting, Philip Franses examines recent developments in time series analysis. The early parts of the book focus on the typical features of time series data in business and economics. Part III is concerned with the discussion of some important concepts in time series analysis, the discussion focuses on the techniques which can be readily applied in practice. Parts IV-VIII suggest different modeling methods and model structures. Part IX extends the concepts in chapter three to multivariate time series. Part X examines common aspects across time series.
Non Linear Time Series Models In Empirical Finance Forecasting
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Author : Philip Hans Franses
language : en
Publisher:
Release Date : 2000
Non Linear Time Series Models In Empirical Finance Forecasting written by Philip Hans Franses and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Elements Of Nonlinear Time Series Analysis And Forecasting
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Author : Jan G. De Gooijer
language : en
Publisher: Springer
Release Date : 2017-03-30
Elements Of Nonlinear Time Series Analysis And Forecasting written by Jan G. De Gooijer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-30 with Mathematics categories.
This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.
Modeling Financial Time Series With S Plus
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Author : Eric Zivot
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Modeling Financial Time Series With S Plus written by Eric Zivot and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Business & Economics categories.
The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.
Nonlinear Time Series
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Author : Randal Douc
language : en
Publisher: CRC Press
Release Date : 2014-01-06
Nonlinear Time Series written by Randal Douc and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-06 with Mathematics categories.
This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.
Non Linear Time Series
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Author : Kamil Feridun Turkman
language : en
Publisher: Springer
Release Date : 2014-09-29
Non Linear Time Series written by Kamil Feridun Turkman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-29 with Mathematics categories.
This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.