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Analysis Of Financial Time Series

Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 0471746185
Size: 18.24 MB
Format: PDF
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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.

Analysis Of Financial Time Series

Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 9781118017098
Size: 46.94 MB
Format: PDF, Docs
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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.

Multivariate Time Series Analysis

Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1118617754
Size: 26.81 MB
Format: PDF, ePub, Docs
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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.

An Introduction To Analysis Of Financial Data With R

Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1119013461
Size: 44.33 MB
Format: PDF, ePub
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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.

Analysis Of Financial Time Series 2nd Ed

Author: Ruey S. Tsay
Publisher:
ISBN: 9788126523696
Size: 58.84 MB
Format: PDF, Kindle
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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.

The Econometric Modelling Of Financial Time Series

Author: Terence C. Mills
Publisher: Cambridge University Press
ISBN: 1139470817
Size: 60.64 MB
Format: PDF, Kindle
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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.

Financial Time Series Analysis With Matlab

Author: J. Abell
Publisher: CreateSpace
ISBN: 9781502358271
Size: 11.28 MB
Format: PDF
View: 6648
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MATLAB Financial Toolbox provides functions for mathematical modeling and statistical analysis of financial data. You can optimize portfolios of financial instruments, optionally taking into account turnover and transaction costs. The toolbox enables you to estimate risk, analyze interest rate levels, price equity and interest rate derivatives, and measure investment performance. Time series analysis capabilities let you perform transformations or regressions with missing data and convert between different trading calendars and day-count conventions.The major themes developed in this book are:Common Problems in Finance Sensitivity of Bond Prices to Interest Rates Bond Portfolio for Hedging Duration and Convexity Bond Prices and Parallel Shifts in Yield Curve Bond Prices and Nonparallel Shifts in Yield Curve Greek-Neutral Portfolios of European Stock Options Term Structure Analysis and Interest-Rate Swaps Plotting an Efficient Frontier Plotting Sensitivities of an Option Plotting Sensitivities of a Portfolio of Options Financial Time Series AnalysisAnalyzing Financial Time Series Creating Financial Time Series Objects Visualizing Financial Time Series Objects Using chartfts Zoom Tool Combine Axes ToolUsing Financial Time SeriesWorking with Financial Time Series Objects Financial Time Series Object Structure Indexing a Financial Time Series Object Financial Time Series Operations Using Time Series to Predict Equity Return Create Financial Time Series Objects Create Closing Prices Adjustment Series Adjust Closing Prices and Make Them Spot Prices Create Return Series Regress Return Series Against Metric Data Plot the Results Calculate the Dividend Rate Financial Time Series Tool (FTSTool)Getting Started with FTSTool Loading Data with FTSTool Using FTSTool for Supported Tasks Creating a Financial Time Series Object Merge Financial Time Series Objects Converting a Financial Time Series Object to a MATLABDouble-Precision Matrix Plotting the Output in Several Formats Viewing Data for a Financial Time Series Object in the Data Table Modifying Data for a Financial Time Series Object in the Data Table Viewing and Modifying the Properties for a FINTS Object Using FTSTool with Other Time Series GUIs Financial Time Series Graphical User Interface Using the Financial Time Series GUI Data Menu Analysis Menu Graphs Menu Saving Time Series DataTrading Date UtilitiesTrading Calendars Graphical User Interface UICalendar Graphical User Interface Technical AnalysisTechnical Indicators