Time Series Analysis

Lehrinhalte

Types of univariate time series models in discrete time: AR-, MA-, ARMA-, ARIMA-processes; estimation and testing of univariate models using financial time series, types of multivariate time series models in discrete time: VAR-, VARMA-, VARIMA-processes; ARCH- and GARCH-models; estimation and testing of multivariate models using financial time series; integration and cointegration

Art der Vermittlung

Präsenzveranstaltung

Art der Veranstaltung

Pflichtfach

Empfohlene Fachliteratur

Alexander, C., 2008, Practical Financial Econometrics; Brockwell, P., Davis, R., 1991, Time Series: Theory and Methods, 2nd ed., Springer; Brockwell, P., Davis, R., 2016, Introduction to Time Series and Forecasting, 3rd ed., Springer; Franses, P., van Dijk, D., 2000, Nonlinear time series models in empirical finance, Cambridge University Press; Shumway, R., Stoffer, D., 2017, Time Series Analysis and its Applications, 4th ed., Springer; Taylor, S., 2005, Asset Price Dynamics, Volatility, and Prediction, University Press of CA; Tsay, R., 2010, Analysis of Financial Time Series, 3rd ed., John Wiley

Lern- und Lehrmethode

Interactive teaching (lecture and discussion), review of coursework problems, application of models on practical problem sets

Prüfungsmethode

30% class participation (coursework problems, presentation of coursework solutions and problems worked out in class, group work activities, mini quizzes), 70% written final exam

Voraussetzungen laut Lehrplan

FOEC10, FUFI10, FUMS10, PRDA10

Schnellinfos

Studiengang

Quantitative Asset and Risk Management (Master)

Akademischer Grad

Master

ECTS Credits

3.00

Unterrichtssprache

Englisch

Studienplan

Berufsbegleitend

Studienjahr, in dem die Lerneinheit angeboten wird

2023

Semester in dem die Lehrveranstaltung angeboten wird

1 WS

Incoming

Ja

Lernergebnisse der Lehrveranstaltung

After the successful completion of the course, students are familiar with basic time series models, i.e. they can list and recognise the models, can write down the models and describe their basic properties. In addition, they are able to analyse, model and simulate financial time series data (at a basic level) using computer programs such as EViews. Students can explain in which areas of asset and risk management time series models are used.

Kennzahl der Lehrveranstaltung

0613-09-01-BB-EN-06