Analysis of Financial Time Series

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Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 9781118017098

Category: Mathematics

Page: 720

View: 7203

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

An Introduction to Analysis of Financial Data with R

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Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 1119013461

Category: Business & Economics

Page: 416

View: 3535

A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including: Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques. An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.

Einführung in die Statistik der Finanzmärkte

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Author: Jürgen Franke,Wolfgang Karl Härdle,Christian Matthias Hafner

Publisher: Springer-Verlag

ISBN: 3642170498

Category: Business & Economics

Page: 428

View: 9523

Multivariate Time Series Analysis

With R and Financial Applications

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Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 1118617754

Category: Mathematics

Page: 520

View: 7969

An accessible guide to the multivariate time series toolsused in numerous real-world applications Multivariate Time Series Analysis: With R and FinancialApplications is the much anticipated sequel coming from one ofthe most influential and prominent experts on the topic of timeseries. Through a fundamental balance of theory and methodology,the book supplies readers with a comprehensible approach tofinancial econometric models and their applications to real-worldempirical research. Differing from the traditional approach to multivariate timeseries, the book focuses on reader comprehension by emphasizingstructural specification, which results in simplified parsimoniousVAR MA modeling. Multivariate Time Series Analysis: With R andFinancial Applications utilizes the freely available Rsoftware package to explore complex data and illustrate relatedcomputation and analyses. Featuring the techniques and methodologyof multivariate linear time series, stationary VAR models, VAR MAtime series and models, unitroot process, factor models, andfactor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce thepresented content • User-friendly R subroutines and research presentedthroughout to demonstrate modern applications • Numerous datasets and subroutines to provide readerswith a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbookfor graduate-level courses on time series and quantitative financeand upper-undergraduate level statistics courses in time series.The book is also an indispensable reference for researchers andpractitioners in business, finance, and econometrics.

ANALYSIS OF FINANCIAL TIME SERIES, 2ND ED

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Author: Ruey S. Tsay

Publisher: N.A

ISBN: 9788126523696

Category:

Page: 628

View: 5957

Market_Desc: Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance Special Features: · Timely topics and recent results include: Value at Risk (VaR); high-frequency financial data analysis; MCMC methods; derivative pricing using jump diffusion with closed-form formulas; VaR calculation using extreme value theory based on nonhomogeneous two-dimensional Poisson process; and multivariate volatility models with time-varying correlations.· New topics to this edition include: Finmetrics in S-plus; estimation of stochastic diffusion equations for derivative pricing; use of realized volatilities; state=space model; and Kalman filter.· The second edition also includes new developments in financial econometrics and more examples of applications in finance.· Emphasis is placed on empirical financial data.· Chapter exercises have been increased in an effort to further reinforce the methods and applications in the text. About The Book: This book provides a comprehensive and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series, and gain experience in financial applications of various econometric methods.

The Econometric Modelling of Financial Time Series

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Author: Terence C Mills,Terence C. Mills

Publisher: Cambridge University Press

ISBN: 9780521624923

Category: Business & Economics

Page: 372

View: 3009

Fully revised second edition of the best-selling graduate and practitioner text.

Angewandte Zeitreihenanalyse mit R

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Author: Rainer Schlittgen

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 311041399X

Category: Business & Economics

Page: 329

View: 5876

Dieses Buch präsentiert die wichtigsten Modelle und Verfahren der Zeitreihenanalyse. Der Schwerpunkt liegt auf dem Zeitbereich; speziell werden explorative Methoden, ARMA-Modelle mit ihren Erweiterungen, Prognosemethoden und Zeitreihenregressionen behandelt. Die Neuauflage wurde akualisiert und unter anderem um ein Kapitel der Long-Memory-Prozesse erweitert.

Econometric Analysis of Financial and Economic Time Series

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Author: Thomas B. Fomby,Dek Terrell,R. Carter Hill

Publisher: Emerald Group Publishing

ISBN: 0762312742

Category: Business & Economics

Page: 408

View: 4135

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.

Nonlinear Time Series Analysis of Economic and Financial Data

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Author: Philip Rothman

Publisher: Springer Science & Business Media

ISBN: 1461551293

Category: Business & Economics

Page: 373

View: 6288

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.

Nonlinear Time Series Analysis

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Author: Ruey S. Tsay,Rong Chen

Publisher: Wiley

ISBN: 1119264057

Category: Mathematics

Page: 512

View: 3542

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.

Operations Research

Formeln und Methoden

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Author: Wolfgang Grundmann

Publisher: Springer-Verlag

ISBN: 3322800474

Category: Business & Economics

Page: 183

View: 5046

Diese Formel- und Methodensammlung enthält in kompakter, übersichtlicher Form mathematische Modelle wesentlicher Problemstellungen des Operations Research sowie Lösungsverfahren. Das thematische Spektrum reicht von den mathematischen Grundlagen über die vielfältigen Fragestellungen der Optimierung bis zu den abschließenden Kapiteln Bedienungstheorie und Lagerhaltung.

Modeling Financial Time Series with S-PLUS

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Author: Eric Zivot,Jiahui Wang

Publisher: Springer Science & Business Media

ISBN: 0387217630

Category: Business & Economics

Page: 632

View: 5148

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.

Zeitreihenmodelle

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Author: Andrew C. Harvey

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3486786741

Category: Business & Economics

Page: 396

View: 8375

Gegenstand des Werkes sind Analyse und Modellierung von Zeitreihen. Es wendet sich an Studierende und Praktiker aller Disziplinen, in denen Zeitreihenbeobachtungen wichtig sind.

Handbook of Financial Time Series

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Author: Torben Gustav Andersen,Richard A. Davis,Jens-Peter Kreiß,Thomas V. Mikosch

Publisher: Springer Science & Business Media

ISBN: 3540712976

Category: Business & Economics

Page: 1050

View: 9178

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.

Econometric Analysis of Financial Markets

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Author: Jürgen Kaehler,Peter Kugler

Publisher: Springer Science & Business Media

ISBN: 3642486665

Category: Business & Economics

Page: 230

View: 9112

This collection of papers represents the state of the art in the applicationof recent econometric methods to the analysis of financial markets. From a methodological point of view the main emphasis is on cointegration analysis and ARCH modelling. In cointegration analysis the links between long-runcomponents of time series are studied. The methods used can be applied to the determination of equilibrium relationships between the variables, whereas ARCH models are concerned with the measurement and analysis of changing variances in time series. These econometric models have been the most significant innovations for the empirical analysis of financial time series in recent years. Other econometric methods and models applied in the papers include factor analysis, vector autoregressions, and Markov-switching models. The papers cover a wide range of issues and theories in financial and international economics: the term structure ofinterest rates, exchange-rate determination, target-zone dynamics, stock-market efficiency, and option pricing.

Nonlinear Time Series Analysis with Applications to Foreign Exchange Rate Volatility

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Author: Christian Hafner

Publisher: Springer Science & Business Media

ISBN: 3662126052

Category: Business & Economics

Page: 222

View: 916

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.