http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
1 online resource (xxiii, 677 pages) : illustrations
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.
Financial time series and their characteristics -- Linear time series analysis and its applications -- Conditional heteroscedastic models -- Nonlinear models and their applications -- High-frequency data analysis and market microstructure -- Continuous-time models and their applications -- Extreme values, quantiles, and value at risk -- Multivariate time series analysis and its applications -- Principal component analysis and factor models -- Multivariate volatility models and their applications -- State-space models and Kalman filter -- Markov chain Monte Carlo methods with applications.
Includes bibliographical references and index.
Wiley series in probability and statistics