Analysis of Financial Time Series

Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 9781118017098

Category: Mathematics

Page: 720

View: 4968

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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.

Analysis of Financial Time Series

Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 0471746185

Category: Business & Economics

Page: 576

View: 5406

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Provides statistical tools and techniques needed to understandtoday's financial markets The Second Edition of this critically acclaimed text provides acomprehensive and systematic introduction to financial econometricmodels and their applications in modeling and predicting financialtime series data. This latest edition continues to emphasizeempirical financial data and focuses on real-world examples.Following this approach, readers will master key aspects offinancial time series, including volatility modeling, neuralnetwork applications, market microstructure and high-frequencyfinancial data, continuous-time models and Ito's Lemma, Value atRisk, multiple returns analysis, financial factor models, andeconometric modeling via computation-intensive methods. The author begins with the basic characteristics of financialtime series data, setting the foundation for the three maintopics: Analysis and application of univariate financial timeseries Return series of multiple assets Bayesian inference in finance methods This new edition is a thoroughly revised and updated text,including the addition of S-Plus® commands and illustrations.Exercises have been thoroughly updated and expanded and include themost current data, providing readers with more opportunities to putthe models and methods into practice. Among the new material addedto the text, readers will find: Consistent covariance estimation under heteroscedasticity andserial correlation Alternative approaches to volatility modeling Financial factor models State-space models Kalman filtering Estimation of stochastic diffusion models The tools provided in this text aid readers in developing adeeper understanding of financial markets through firsthandexperience in working with financial data. This is an idealtextbook for MBA students as well as a reference for researchersand professionals in business and finance.

Multivariate Time Series Analysis

With R and Financial Applications

Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 1118617754

Category: Mathematics

Page: 520

View: 4312

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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

Author: Ruey S. Tsay

Publisher: N.A

ISBN: 9788126523696

Category:

Page: 628

View: 8180

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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.

An Introduction to Analysis of Financial Data with R

Author: Ruey S. Tsay

Publisher: John Wiley & Sons

ISBN: 1119013461

Category: Business & Economics

Page: 416

View: 1920

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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.

The Econometric Modelling of Financial Time Series

Author: Terence C. Mills,Raphael N. Markellos

Publisher: Cambridge University Press

ISBN: 1139470817

Category: Business & Economics

Page: 468

View: 1585

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Terence Mills' best-selling graduate textbook provides detailed coverage of research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. This third edition, co-authored with Raphael Markellos, contains a wealth of material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.

Modeling Financial Time Series with S-PLUS

Author: Eric Zivot,Jiahui Wang

Publisher: Springer Science & Business Media

ISBN: 0387217630

Category: Business & Economics

Page: 632

View: 9935

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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.

Angewandte Zeitreihenanalyse mit R

Author: Rainer Schlittgen

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 311041399X

Category: Business & Economics

Page: 329

View: 9922

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Dieses Buch präsentiert die wichtigsten Modelle und Verfahren der Zeitreihenanalyse in einer für Studierende und Anwender leicht zugänglichen Form. Der Schwerpunkt liegt auf dem Zeitbereich; speziell werden explorative Methoden, ARMA-Modelle mit ihren Erweiterungen, Prognosemethoden und Zeitreihenregressionen behandelt. Auch der Frequenzbereich wird vorgestellt. Weiter werden multivariate Zeitreihen, Zustandsraummodelle und Modelle für Heteroskedastizität behandelt. Die Methoden werden überwiegend anhand einfacher Situationen verdeutlicht und mittels zahlreicher realer Beispiele illustriert. Die Beispiele stammen aus den Bereichen Wirtschaftswissenschaften, Biologie, Geologie, Medizin und Meteorologie. Die umfassende Erfahrung des Autors auf dem Gebiet der Zeitreihenanalyse fließt an vielen Stellen in Form von Anwendungstipps ein. Dieser Text zur Zeitreihenanalyse ist der erste im deutschsprachigen Bereich, der auf der freien statistischen Programmierumgebung R basiert. In einem eigenen Kapitel wird eine kurze Einführung gegeben. Bei den Beispielen wird der zugehörige Code jeweils angegeben und kommentiert. Zudem enthält jedes Kapitel eine Übersicht über die entsprechenden R-Funktionen der verschiedenen R-Pakete. Die Neuauflage wurde akualisiert und unter anderem um ein Kapitel zu der Long-Memory-Prozessen erweitert.

Handbook of Financial Time Series

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: 2728

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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.

Nonlinear Time Series Analysis

Author: Ruey S. Tsay,Rong Chen

Publisher: Wiley

ISBN: 1119264057

Category: Mathematics

Page: 512

View: 8647

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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.

Nonlinear Time Series Analysis of Economic and Financial Data

Author: Philip Rothman

Publisher: Springer Science & Business Media

ISBN: 1461551293

Category: Business & Economics

Page: 373

View: 9210

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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.

Zeitreihenmodelle

Author: Andrew C. Harvey

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3486786741

Category: Business & Economics

Page: 396

View: 5515

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

Operations Research

Formeln und Methoden

Author: Wolfgang Grundmann

Publisher: Springer-Verlag

ISBN: 3322800474

Category: Business & Economics

Page: 183

View: 9318

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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.

Mein Kampf

Author: Adolf Hitler

Publisher: N.A

ISBN: 9781911417682

Category:

Page: N.A

View: 4370

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Als glUckliche Bestimmung gilt es mir heute, da das Schicksal mir zum Geburtsort gerade Braunau am Inn zuwies. Liegt doch dieses StAdtchen an der Grenze jener zwei deutschen Staaten, deren Wiedervereinigung mindestens uns JUngeren als eine mit allen Mitteln durchzufUhrende Lebensaufgabe erscheint! DeutschOsterreich mu wieder zurUck zum groen deutschen Mutterlande, und zwar nicht aus GrUnden irgendwelcher wirtschaftlichen ErwAgungen heraus. Nein, nein: Auch wenn diese Vereinigung, wirtschaftlich gedacht, gleichgUltig, ja selbst wenn sie schAdlich wAre, sie mUte dennoch stattfinden. Gleiches Blut gehOrt in ein gemeinsames Reich. Das deutsche Volk besitzt solange kein moralisches Recht zu kolonialpolitischer TAtigkeit, solange es nicht einmal seine eigenen SOhne in einem gemeinsamen Staat zu fassen vermag. Erst wenn des Reiches Grenze auch den letzten Deutschen umschliet, ohne mehr die Sicherheit seiner ErnAhrung bieten zu kOnnen, ersteht aus der Not des eigenen Volkes das moralische Recht zur Erwerbung fremden Grund und Bodens. Der Pflug ist dann das Schwert, und aus den TrAnen des Krieges erwAchst fUr die Nach welt das tAgliche Brot. So scheint mir dieses kleine GrenzstAdtchen das Symbol einer groen Aufgabe zu sein.