Parameter Estimation In Nonlinear Ar Garch Models

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Modelling Nonlinear Economic Time Series

Author : Timo Teräsvirta
Publisher : OUP Oxford
ISBN 13 : 9780199587148
Total Pages : 592 pages
Book Rating : 4.5/5 (871 download)

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Book Synopsis Modelling Nonlinear Economic Time Series by : Timo Teräsvirta

Download or read book Modelling Nonlinear Economic Time Series written by Timo Teräsvirta and published by OUP Oxford. This book was released on 2010-12-16 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For thispurpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried outusing numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter isdevoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.

Handbook of Volatility Models and Their Applications

Author : Luc Bauwens
Publisher : John Wiley & Sons
ISBN 13 : 0470872519
Total Pages : 566 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Handbook of Volatility Models and Their Applications by : Luc Bauwens

Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-04-17 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

A Time Series Approach to Option Pricing

Author : Christophe Chorro
Publisher : Springer
ISBN 13 : 3662450372
Total Pages : 202 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis A Time Series Approach to Option Pricing by : Christophe Chorro

Download or read book A Time Series Approach to Option Pricing written by Christophe Chorro and published by Springer. This book was released on 2014-12-04 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current world financial scene indicates at an intertwined and interdependent relationship between financial market activity and economic health. This book explains how the economic messages delivered by the dynamic evolution of financial asset returns are strongly related to option prices. The Black Scholes framework is introduced and by underlining its shortcomings, an alternative approach is presented that has emerged over the past ten years of academic research, an approach that is much more grounded on a realistic statistical analysis of data rather than on ad hoc tractable continuous time option pricing models. The reader then learns what it takes to understand and implement these option pricing models based on time series analysis in a self-contained way. The discussion covers modeling choices available to the quantitative analyst, as well as the tools to decide upon a particular model based on the historical datasets of financial returns. The reader is then guided into numerical deduction of option prices from these models and illustrations with real examples are used to reflect the accuracy of the approach using datasets of options on equity indices.

Time Series Analysis: Methods and Applications

Author : Tata Subba Rao
Publisher : Elsevier
ISBN 13 : 0444538585
Total Pages : 778 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Time Series Analysis: Methods and Applications by : Tata Subba Rao

Download or read book Time Series Analysis: Methods and Applications written by Tata Subba Rao and published by Elsevier. This book was released on 2012-06-26 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.

GARCH Models

Author : Christian Francq
Publisher : John Wiley & Sons
ISBN 13 : 1119313562
Total Pages : 507 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis GARCH Models by : Christian Francq

Download or read book GARCH Models written by Christian Francq and published by John Wiley & Sons. This book was released on 2019-03-19 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation, and tests. The book also provides new coverage of several extensions such as multivariate models, looks at financial applications, and explores the very validation of the models used. GARCH Models: Structure, Statistical Inference and Financial Applications, 2nd Edition features a new chapter on Parameter-Driven Volatility Models, which covers Stochastic Volatility Models and Markov Switching Volatility Models. A second new chapter titled Alternative Models for the Conditional Variance contains a section on Stochastic Recurrence Equations and additional material on EGARCH, Log-GARCH, GAS, MIDAS, and intraday volatility models, among others. The book is also updated with a more complete discussion of multivariate GARCH; a new section on Cholesky GARCH; a larger emphasis on the inference of multivariate GARCH models; a new set of corrected problems available online; and an up-to-date list of references. Features up-to-date coverage of the current research in the probability, statistics, and econometric theory of GARCH models Covers significant developments in the field, especially in multivariate models Contains completely renewed chapters with new topics and results Handles both theoretical and applied aspects Applies to researchers in different fields (time series, econometrics, finance) Includes numerous illustrations and applications to real financial series Presents a large collection of exercises with corrections Supplemented by a supporting website featuring R codes, Fortran programs, data sets and Problems with corrections GARCH Models, 2nd Edition is an authoritative, state-of-the-art reference that is ideal for graduate students, researchers, and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.

Elements of Nonlinear Time Series Analysis and Forecasting

Author : Jan G. De Gooijer
Publisher : Springer
ISBN 13 : 3319432524
Total Pages : 626 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Elements of Nonlinear Time Series Analysis and Forecasting by : Jan G. De Gooijer

Download or read book Elements of Nonlinear Time Series Analysis and Forecasting written by Jan G. De Gooijer and published by Springer. This book was released on 2017-03-30 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Time Series Analysis: Methods and Applications

Author :
Publisher : Elsevier
ISBN 13 : 0444538631
Total Pages : 777 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Time Series Analysis: Methods and Applications by :

Download or read book Time Series Analysis: Methods and Applications written by and published by Elsevier. This book was released on 2012-05-18 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. - Comprehensively presents the various aspects of statistical methodology - Discusses a wide variety of diverse applications and recent developments - Contributors are internationally renowened experts in their respective areas

Financial Risk Management with Bayesian Estimation of GARCH Models

Author : David Ardia
Publisher : Springer Science & Business Media
ISBN 13 : 3540786570
Total Pages : 206 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Financial Risk Management with Bayesian Estimation of GARCH Models by : David Ardia

Download or read book Financial Risk Management with Bayesian Estimation of GARCH Models written by David Ardia and published by Springer Science & Business Media. This book was released on 2008-05-08 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.

Essays in Nonlinear Time Series Econometrics

Author : Niels Haldrup
Publisher : Oxford University Press, USA
ISBN 13 : 0199679959
Total Pages : 393 pages
Book Rating : 4.1/5 (996 download)

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Book Synopsis Essays in Nonlinear Time Series Econometrics by : Niels Haldrup

Download or read book Essays in Nonlinear Time Series Econometrics written by Niels Haldrup and published by Oxford University Press, USA. This book was released on 2014-05 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: A book on nonlinear economic relations that involve time. It covers specification testing of linear versus non-linear models, model specification testing, estimation of smooth transition models, volatility modelling using non-linear model specification, analysis of high dimensional data set, and forecasting.

Computational Finance and Financial Econometrics

Author : Eric Zivot
Publisher : CRC Press
ISBN 13 : 9781498775779
Total Pages : 500 pages
Book Rating : 4.7/5 (757 download)

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Book Synopsis Computational Finance and Financial Econometrics by : Eric Zivot

Download or read book Computational Finance and Financial Econometrics written by Eric Zivot and published by CRC Press. This book was released on 2017-01-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. The author explains how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios.

Parameter Estimation in Stochastic Volatility Models

Author : Jaya P. N. Bishwal
Publisher : Springer Nature
ISBN 13 : 3031038614
Total Pages : 634 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Parameter Estimation in Stochastic Volatility Models by : Jaya P. N. Bishwal

Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.

Handbook of Financial Time Series

Author : Torben Gustav Andersen
Publisher : Springer Science & Business Media
ISBN 13 : 3540712976
Total Pages : 1045 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen

Download or read book Handbook of Financial Time Series written by Torben Gustav Andersen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics

Author : Burcu Adıgüzel Mercangöz
Publisher : Springer Nature
ISBN 13 : 3030541088
Total Pages : 465 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics by : Burcu Adıgüzel Mercangöz

Download or read book Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics written by Burcu Adıgüzel Mercangöz and published by Springer Nature. This book was released on 2021-02-17 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook presents emerging research exploring the theoretical and practical aspects of econometric techniques for the financial sector and their applications in economics. By doing so, it offers invaluable tools for predicting and weighing the risks of multiple investments by incorporating data analysis. Throughout the book the authors address a broad range of topics such as predictive analysis, monetary policy, economic growth, systemic risk and investment behavior. This book is a must-read for researchers, scholars and practitioners in the field of economics who are interested in a better understanding of current research on the application of econometric methods to financial sector data.

Evolutionary Statistical Procedures

Author : Roberto Baragona
Publisher : Springer Science & Business Media
ISBN 13 : 3642162185
Total Pages : 283 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Evolutionary Statistical Procedures by : Roberto Baragona

Download or read book Evolutionary Statistical Procedures written by Roberto Baragona and published by Springer Science & Business Media. This book was released on 2011-01-03 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions are infeasible. Evolutionary algorithms represent a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid crosses of these procedures with standard statistical algorithms like Metropolis-Hastings) in a variety of applications. This book would serve as an excellent reference work for statistical researchers at an advanced graduate level or beyond, particularly those with a strong background in computer science.

Forecasting in the Presence of Structural Breaks and Model Uncertainty

Author : David E. Rapach
Publisher : Emerald Group Publishing
ISBN 13 : 1849505403
Total Pages : 691 pages
Book Rating : 4.8/5 (495 download)

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Book Synopsis Forecasting in the Presence of Structural Breaks and Model Uncertainty by : David E. Rapach

Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.

Non-Linear Time Series Models in Empirical Finance

Author : Philip Hans Franses
Publisher : Cambridge University Press
ISBN 13 : 0521770416
Total Pages : 299 pages
Book Rating : 4.5/5 (217 download)

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Book Synopsis Non-Linear Time Series Models in Empirical Finance by : Philip Hans Franses

Download or read book Non-Linear Time Series Models in Empirical Finance written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2000-07-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2000 volume reviews non-linear time series models, and their applications to financial markets.

EEG Signal Processing and Machine Learning

Author : Saeid Sanei
Publisher : John Wiley & Sons
ISBN 13 : 1119386942
Total Pages : 756 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis EEG Signal Processing and Machine Learning by : Saeid Sanei

Download or read book EEG Signal Processing and Machine Learning written by Saeid Sanei and published by John Wiley & Sons. This book was released on 2021-09-27 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: EEG Signal Processing and Machine Learning Explore cutting edge techniques at the forefront of electroencephalogram research and artificial intelligence from leading voices in the field The newly revised Second Edition of EEG Signal Processing and Machine Learning delivers an inclusive and thorough exploration of new techniques and outcomes in electroencephalogram (EEG) research in the areas of analysis, processing, and decision making about a variety of brain states, abnormalities, and disorders using advanced signal processing and machine learning techniques. The book content is substantially increased upon that of the first edition and, while it retains what made the first edition so popular, is composed of more than 50% new material. The distinguished authors have included new material on tensors for EEG analysis and sensor fusion, as well as new chapters on mental fatigue, sleep, seizure, neurodevelopmental diseases, BCI, and psychiatric abnormalities. In addition to including a comprehensive chapter on machine learning, machine learning applications have been added to almost all the chapters. Moreover, multimodal brain screening, such as EEG-fMRI, and brain connectivity have been included as two new chapters in this new edition. Readers will also benefit from the inclusion of: A thorough introduction to EEGs, including neural activities, action potentials, EEG generation, brain rhythms, and EEG recording and measurement An exploration of brain waves, including their generation, recording, and instrumentation, abnormal EEG patterns and the effects of ageing and mental disorders A treatment of mathematical models for normal and abnormal EEGs Discussions of the fundamentals of EEG signal processing, including statistical properties, linear and nonlinear systems, frequency domain approaches, tensor factorization, diffusion adaptive filtering, deep neural networks, and complex-valued signal processing Perfect for biomedical engineers, neuroscientists, neurophysiologists, psychiatrists, engineers, students and researchers in the above areas, the Second Edition of EEG Signal Processing and Machine Learning will also earn a place in the libraries of undergraduate and postgraduate students studying Biomedical Engineering, Neuroscience and Epileptology.