Financial time series

Course PM

This page contains the program of the course: lectures, exercise sessions and projects. Other information, such as learning outcomes, teachers, literature and examination, are in a separate course PM.

Program

The schedule of the course is in TimeEdit.

The following program is preliminary and may be updated as the course progresses. Check the course page regularly!

Lectures

Day Sections Content
24/3 Introduction to the course, to time series and stationarity
26/3 [BD] 2.1, 2.4 Characterization of stationarity
31/3 [BD] 1.6, 2.5 Hypothesis testing, forecasting time series
2/4 [BD] 2.5 Forecasting stationary time series
21/4 [BD] 1.5, 2.2 Trend and seasonality, linear processes
23/4 [BD] 3.1-3.2 ARMA processes (causality, invertibility, ACVF)
28/4 [BD] 3.1-3.2, 5.1-5.2 ARMA processes (PACF, parameter estimation)
5/5 [BD] 3.3, 5.3-5.5, 6.1, 6.3 ARMA processes (order identification, model building, forecasting, ARIMA, unit roots)
7/5 [BD] 7.1-7.2, [T] 3 (G)ARCH processes
12/5 [BD] 7.1-7.3, [T] 3 (G)ARCH processes
14/5 [T] 3.6, 4.1 [BD] 7.3 IGARCH processes, nonlinear models
19/5 [T] 4.1, 4.2 Nonparametric models, testing for nonlinearities
26/5 [T] 4.4 Nonparametric forecasting
28/5 Old exams and course evaluation 

 

Recommended exercises

Day Exercises
27/3 [BD] 1.1, 1.3*, 1.4, 1.6, 1.7 and exercises in basic probability, at least 1-4. One or two of these extra exercises will also be covered on the blackboard.
3/4 [BD] 2.1, 2.2, 2.3, 2.4, 2.7, 2.8, 2.14ab, 2.15, 2.20, 2.21
24/4 [BD] 1.10, 1.11, 1.12a, 1.13, 1.15, 3.1abcde, 3.3abcde, 3.6, 3.7, 3.8.
8/5 [BD] 3.4, 3.11, 5.3, 5.4abde, 5.8, 5.11, 5.12, 6.1. 
15/5 [BD] 1.8  and additional ARCH and GARCH exercises (2, 4, and 6 will be covered).
29/5 Non-linear model exercises.

Exercises in bold will be covered on the blackboard during excercise sessions. You are expected to try to solve them on your own before the session. 
* You may assume that the process has densities associated with its finite dimensional distributions.

Projects

 

Course summary:

Date Details Due