401-4623-DRL Time Series Analysis
| Semester | Autumn Semester 2023 |
| Lecturers | N. Meinshausen |
| Periodicity | two-yearly recurring course |
| Course | Does not take place this semester. |
| Language of instruction | English |
| Comment | Only for ZGSM (ETH D-MATH and UZH I-MATH) doctoral students. The latter need to register at myStudies and then send an email to info@zgsm.ch with their name, course number and student ID. Please see https://zgsm.math.uzh.ch/index.php?id=forum0 |
| Abstract | The course offers an introduction into analyzing times series, that is observations which occur in time. The material will cover Stationary Models, ARMA processes, Spectral Analysis, Forecasting, Nonstationary Models, ARIMA Models and an introduction to GARCH models. |
| Learning objective | The goal of the course is to have a a good overview of the different types of time series and the approaches used in their statistical analysis. |
| Content | This course treats modeling and analysis of time series, that is random variables which change in time. As opposed to the i.i.d. framework, the main feature exibited by time series is the dependence between successive observations. The key topics which will be covered as: Stationarity Autocorrelation Trend estimation Elimination of seasonality Spectral analysis, spectral densities Forecasting ARMA, ARIMA, Introduction into GARCH models |
| Literature | The main reference for this course is the book "Introduction to Time Series and Forecasting", by P. J. Brockwell and R. A. Davis |
| Prerequisites / Notice | Basic knowledge in probability and statistics |