000			02667nam a22002057a 4500
005			20250411123011.0
008			250411b |||||||| |||| 00| 0 eng d
020			_a9781009396264
082			_a330.03 _bLIN
100			_aLinton, Oliver B _921234
245			_aTime series for economics and finance
260			_bCambridge University Press _aNew York _c2025
300			_axxii, 430 p.
365			_aGBP _b44.99
500			_aTable of contents: Frontmatter 1 - Introduction pp 1-13 2 - Stationarity and Mixing pp 14-41 3 - Linear Time Series Models pp 42-101 4 - Spectral Analysis pp 102-128 5 - Inference under Heterogeneity and Weak Dependence pp 129-150 6 - Nonstationary Processes, Trends, and Seasonality pp 151-195 7 - Multivariate Linear Time Series pp 196-237 8 - State Space Models and the Kalman Filter pp 238-251 9 - Bayesian Methods pp 252-265 10 - Nonlinear Time Series Models pp 266-302 11 - Nonparametric Methods and Machine Learning pp 303-346 12 - Continuous-Time Processes pp 347-373 13 - Forecasting pp 374-396 Appendices pp 397-410 Appendix A - Fourier Analysis pp 397-397 Appendix B - Matrices and Multivariate Normal pp 398-400 Appendix C - Laws of Large Numbers and Central Limit Theorems pp 401-404 Appendix D - Data and Data Sources pp 405-408 Appendix E - A Short Introduction to EViews pp 409-410 Bibliography pp 411-427 Index (https://www.cambridge.org/highereducation/books/time-series-for-economics-and-finance/149D2AF6A765ACE8DB51D5AEDD0C4AAD#contents)
520			_aFocusing on methods for data that are ordered in time, this textbook provides a comprehensive guide to analyzing time series data using modern techniques from data science. It is specifically tailored to economics and finance applications, aiming to provide students with rigorous training. Chapters cover Bayesian approaches, nonparametric smoothing methods, machine learning, and continuous time econometrics. Theoretical and empirical exercises, concise summaries, bolded key terms, and illustrative examples are included throughout to reinforce key concepts and bolster understanding. Ancillary materials include an instructor's manual with solutions and additional exercises, PowerPoint lecture slides, and datasets. With its clear and accessible style, this textbook is an essential tool for advanced undergraduate and graduate students in economics, finance, and statistics. (https://www.cambridge.org/highereducation/books/time-series-for-economics-and-finance/149D2AF6A765ACE8DB51D5AEDD0C4AAD#overview)
650			_aEconomics
650			_aFinance
942			_cBK _2ddc
999			_c8916 _d8916