Volatility And Time Series Econometrics

Volatility And Time Series Econometrics Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Volatility And Time Series Econometrics book. This book definitely worth reading, it is an incredibly well-written.

Volatility and Time Series Econometrics

Tim Bollerslev,Jeffrey Russell,Mark Watson
Volatility and Time Series Econometrics Book PDF

Author : Tim Bollerslev,Jeffrey Russell,Mark Watson
Publisher : OUP Oxford
Page : 432 pages
File Size : 45,5 Mb
Release : 2010-02-11
Category : Business & Economics
ISBN : 9780191572197

Get Book

Volatility and Time Series Econometrics by Tim Bollerslev,Jeffrey Russell,Mark Watson Pdf

Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally. Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study the behavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.

Volatility and Time Series Econometrics

Mark Watson,Jeffrey Russell,Tim Bollerslev
Volatility and Time Series Econometrics Book PDF

Author : Mark Watson,Jeffrey Russell,Tim Bollerslev
Publisher : Oxford University Press
Page : 432 pages
File Size : 46,5 Mb
Release : 2010-02-11
Category : Business & Economics
ISBN : 9780199549498

Get Book

Volatility and Time Series Econometrics by Mark Watson,Jeffrey Russell,Tim Bollerslev Pdf

A volume that celebrates and develops the work of Nobel Laureate Robert Engle, it includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics

Modelling Financial Time Series

Stephen J. Taylor
Modelling Financial Time Series Book PDF

Author : Stephen J. Taylor
Publisher : World Scientific
Page : 297 pages
File Size : 44,5 Mb
Release : 2008
Category : Business & Economics
ISBN : 9789812770844

Get Book

Modelling Financial Time Series by Stephen J. Taylor Pdf

This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic volatility models that are often used and cited in academic research and are applied by quantitative analysts in many banks. Another often-cited contribution of the first edition is the documentation of statistical characteristics of financial returns, which are referred to as stylized facts.This second edition takes into account the remarkable progress made by empirical researchers during the past two decades from 1986 to 2006. In the new Preface, the author summarizes this progress in two key areas: firstly, measuring, modelling and forecasting volatility; and secondly, detecting and exploiting price trends.

Time Series Econometrics

Klaus Neusser
Time Series Econometrics Book PDF

Author : Klaus Neusser
Publisher : Springer
Page : 421 pages
File Size : 49,6 Mb
Release : 2016-06-14
Category : Business & Economics
ISBN : 9783319328621

Get Book

Time Series Econometrics by Klaus Neusser Pdf

This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.

Dynamic Models for Volatility and Heavy Tails

Andrew C. Harvey
Dynamic Models for Volatility and Heavy Tails Book PDF

Author : Andrew C. Harvey
Publisher : Cambridge University Press
Page : 128 pages
File Size : 47,6 Mb
Release : 2013-04-22
Category : Business & Economics
ISBN : 9781107328785

Get Book

Dynamic Models for Volatility and Heavy Tails by Andrew C. Harvey Pdf

The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.

Handbook of Volatility Models and Their Applications

Luc Bauwens,Christian M. Hafner,Sebastien Laurent
Handbook of Volatility Models and Their Applications Book PDF

Author : Luc Bauwens,Christian M. Hafner,Sebastien Laurent
Publisher : John Wiley & Sons
Page : 566 pages
File Size : 44,9 Mb
Release : 2012-04-17
Category : Business & Economics
ISBN : 9780470872512

Get Book

Handbook of Volatility Models and Their Applications by Luc Bauwens,Christian M. Hafner,Sebastien Laurent Pdf

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.

Time Series Econometrics

John D. Levendis
Time Series Econometrics Book PDF

Author : John D. Levendis
Publisher : Springer
Page : 409 pages
File Size : 42,9 Mb
Release : 2019-01-31
Category : Business & Economics
ISBN : 9783319982823

Get Book

Time Series Econometrics by John D. Levendis Pdf

In this book, the author rejects the theorem-proof approach as much as possible, and emphasize the practical application of econometrics. They show with examples how to calculate and interpret the numerical results. This book begins with students estimating simple univariate models, in a step by step fashion, using the popular Stata software system. Students then test for stationarity, while replicating the actual results from hugely influential papers such as those by Granger and Newbold, and Nelson and Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot and Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Finally, students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger. The book contains many worked-out examples, and many data-driven exercises. While intended primarily for graduate students and advanced undergraduates, practitioners will also find the book useful.

Non-Linear Time Series Models in Empirical Finance

Philip Hans Franses,Dick van Dijk
Non Linear Time Series Models in Empirical Finance Book PDF

Author : Philip Hans Franses,Dick van Dijk
Publisher : Cambridge University Press
Page : 299 pages
File Size : 52,8 Mb
Release : 2000-07-27
Category : Business & Economics
ISBN : 9780521770415

Get Book

Non-Linear Time Series Models in Empirical Finance by Philip Hans Franses,Dick van Dijk Pdf

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

Time Series Models

D.R. Cox,D.V. Hinkley,O.E. Barndorff-Nielsen
Time Series Models Book PDF

Author : D.R. Cox,D.V. Hinkley,O.E. Barndorff-Nielsen
Publisher : CRC Press
Page : 243 pages
File Size : 43,5 Mb
Release : 2020-11-26
Category : Mathematics
ISBN : 9781000152944

Get Book

Time Series Models by D.R. Cox,D.V. Hinkley,O.E. Barndorff-Nielsen Pdf

The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds. The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book. The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader.

Econometric Analysis of Financial and Economic Time Series

Thomas B. Fomby,Dek Terrell,R. Carter Hill
Econometric Analysis of Financial and Economic Time Series Book PDF

Author : Thomas B. Fomby,Dek Terrell,R. Carter Hill
Publisher : Emerald Group Publishing
Page : 407 pages
File Size : 53,5 Mb
Release : 2006-03-01
Category : Business & Economics
ISBN : 9780762312740

Get Book

Econometric Analysis of Financial and Economic Time Series by Thomas B. Fomby,Dek Terrell,R. Carter Hill Pdf

Talks about the time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, application of the technique of boosting in volatility forecasting, and more.

Time Series in Economics and Finance

Tomas Cipra
Time Series in Economics and Finance Book PDF

Author : Tomas Cipra
Publisher : Springer Nature
Page : 409 pages
File Size : 43,9 Mb
Release : 2020-08-31
Category : Business & Economics
ISBN : 9783030463472

Get Book

Time Series in Economics and Finance by Tomas Cipra Pdf

This book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods, such as cointegration and recursive state space modeling. It also includes numerous practical examples to demonstrate the theory using real-world data, as well as exercises at the end of each chapter to aid understanding. This book serves as a reference text for researchers, students and practitioners interested in time series, and can also be used for university courses on econometrics or computational finance.

Modeling Financial Time Series with S-PLUS

Eric Zivot,Jiahui Wang
Modeling Financial Time Series with S PLUS Book PDF

Author : Eric Zivot,Jiahui Wang
Publisher : Springer Science & Business Media
Page : 632 pages
File Size : 48,7 Mb
Release : 2013-11-11
Category : Business & Economics
ISBN : 9780387217635

Get Book

Modeling Financial Time Series with S-PLUS by Eric Zivot,Jiahui Wang Pdf

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.

Dynamic Models for Volatility and Heavy Tails

Andrew C. Harvey
Dynamic Models for Volatility and Heavy Tails Book PDF

Author : Andrew C. Harvey
Publisher : Cambridge University Press
Page : 281 pages
File Size : 48,8 Mb
Release : 2013-04-22
Category : Business & Economics
ISBN : 9781107034723

Get Book

Dynamic Models for Volatility and Heavy Tails by Andrew C. Harvey Pdf

The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.

Missing Data Methods

David M. Drukker
Missing Data Methods Book PDF

Author : David M. Drukker
Publisher : Emerald Group Publishing
Page : 262 pages
File Size : 42,7 Mb
Release : 2011-11-30
Category : Business & Economics
ISBN : 9781780525266

Get Book

Missing Data Methods by David M. Drukker Pdf

Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.

Essays in Nonlinear Time Series Econometrics

Niels Haldrup,Mika Meitz,Pentti Saikkonen
Essays in Nonlinear Time Series Econometrics Book PDF

Author : Niels Haldrup,Mika Meitz,Pentti Saikkonen
Publisher : OUP Oxford
Page : 352 pages
File Size : 43,6 Mb
Release : 2014-06-26
Category : Business & Economics
ISBN : 9780191669545

Get Book

Essays in Nonlinear Time Series Econometrics by Niels Haldrup,Mika Meitz,Pentti Saikkonen Pdf

This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.