Download or read book Volatility and Time Series Econometrics written by Tim Bollerslev and published by OUP Oxford. This book was released on 2010-02-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Volatility and Time Series Econometrics written by Mark Watson and published by Oxford University Press. This book was released on 2010-02-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Time Series Econometrics written by Klaus Neusser and published by Springer. This book was released on 2016-06-14 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Time Series Econometrics written by John D. Levendis and published by Springer. This book was released on 2019-01-31 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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 2012-03-22 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.

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.

Download or read book Time Series Models written by D.R. Cox and published by CRC Press. This book was released on 2020-11-26 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Modelling Financial Time Series written by Stephen J. Taylor and published by World Scientific. This book was released on 2008 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Time Series Econometrics written by Pierre Perron and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Part I. Unit roots and trend breaks -- Part II. Structural change

Download or read book Econometric Analysis of Financial and Economic Time Series written by Thomas B. Fomby and published by Emerald Group Publishing. This book was released on 2006-03-01 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Time Series in Economics and Finance written by Tomas Cipra and published by Springer Nature. This book was released on 2020-08-31 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Introduction to Modern Time Series Analysis written by Gebhard Kirchgässner and published by Springer Science & Business Media. This book was released on 2008-08-27 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.

Download or read book Introduction to Modern Time Series Analysis written by Gebhard Kirchgässner and published by Springer Science & Business Media. This book was released on 2012-10-09 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.

Download or read book Applied Time Series Econometrics written by Helmut Lütkepohl and published by Cambridge University Press. This book was released on 2004-08-02 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.

Download or read book Time Series and Panel Data Econometrics written by M. Hashem Pesaran and published by Oxford University Press, USA. This book was released on 2015 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.

Download or read book Modeling Financial Time Series with S PLUS written by Eric Zivot and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Missing Data Methods written by David M. Drukker and published by Emerald Group Publishing. This book was released on 2011-11-30 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.