Analysis of Financial Time Series (Hardback)Ruey S. Tsay (author)
The author begins with basic characteristics of financial time series data before covering three main topics:Analysis and application of univariate financial time seriesThe return series of multiple assetsBayesian 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.
Publisher: John Wiley & Sons Inc
Number of pages: 720
Weight: 1111 g
Dimensions: 236 x 158 x 38 mm
Edition: 3rd edition
"Nevertheless, all in all the book can be a very useful reference for students as well as for professionals." (Zentralblatt MATH, 2011)
"Factor models, an important technique used in quantitative finance, are given a full treatment with macroeconomic factor models and fundamental factor models.
The coverage of the book is comprehensive. It starts from basic time series techniques and finishes with advanced concepts such as state space models and MCMC methods. There is a balance between the theoretical background necessary to appreciate the nuances and the practical aspect of implementation. More importantly it gives insights about what time series models can't address. The book has an excellent supporting website which has all the programs and data sets which helps to internalize the concepts. Finally, teaching professionals should find the solutions manual as a valuable tool to explain concepts and to ensure understanding." (BookPleasures.com, January 2011)
"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." (Insurance News Net, 8 December 2010)
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