Book contents
- Time Series for Economics and Finance
- Time Series for Economics and Finance
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Notation and Conventions
- 1 Introduction
- 2 Stationarity and Mixing
- 3 Linear Time Series Models
- 4 Spectral Analysis
- 5 Inference under Heterogeneity and Weak Dependence
- 6 Nonstationary Processes, Trends, and Seasonality
- 7 Multivariate Linear Time Series
- 8 State Space Models and the Kalman Filter
- 9 Bayesian Methods
- 10 Nonlinear Time Series Models
- 11 Nonparametric Methods and Machine Learning
- 12 Continuous-Time Processes
- 13 Forecasting
- Book part
- Bibliography
- Index
- References
Bibliography
Published online by Cambridge University Press: 19 December 2024
- Time Series for Economics and Finance
- Time Series for Economics and Finance
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Notation and Conventions
- 1 Introduction
- 2 Stationarity and Mixing
- 3 Linear Time Series Models
- 4 Spectral Analysis
- 5 Inference under Heterogeneity and Weak Dependence
- 6 Nonstationary Processes, Trends, and Seasonality
- 7 Multivariate Linear Time Series
- 8 State Space Models and the Kalman Filter
- 9 Bayesian Methods
- 10 Nonlinear Time Series Models
- 11 Nonparametric Methods and Machine Learning
- 12 Continuous-Time Processes
- 13 Forecasting
- Book part
- Bibliography
- Index
- References
- Type
- Chapter
- Information
- Time Series for Economics and Finance , pp. 411 - 427Publisher: Cambridge University PressPrint publication year: 2024