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Analysis of financial time series

By: Tsay, Ruey S.
Material type: materialTypeLabelBookSeries: Wiley series in probability and statistics.Publisher: Hoboken : John Wiley and Sons, 2010Edition: 3rd ed.Description: xxiii, 677p. ; ill., tables 24 cm.ISBN: 9780470414354.Subject(s): Cointegration | Covariance matrix | Extreme value theory | Daily log returns | Fitted model | GARCH model | Gibbs sampling | Kalman filter | likelihood function | Wiener process | Linear regression | Ljung-Box Test | Posterior distribution | Serial correlations | Stochastic volatility | Wiener processDDC classification: 332.0151955 Summary: 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.
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Books 332.0151955 TSA (Browse shelf) Available 034918

Includes bibliographical references and index.

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.

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