Semester:WS 20/21
Art:Modul
Sprache:Englisch
ECTS-Credits:2.0
Plansemester:1
Lektionen / Semester:21.0 L / 16.0 h
Selbststudium:44.0 h
Art:Modul
Sprache:Englisch
ECTS-Credits:2.0
Plansemester:1
Lektionen / Semester:21.0 L / 16.0 h
Selbststudium:44.0 h
Modulleitung/Dozierende
- Ass.-Prof. Dr. Sebastian Stöckl
(Modulleitung)
Studiengang
Masterstudium Finance (01.09.2020)Lehrveranstaltungen
Beschreibung
- Financial data: diagnostic tests, pitfalls and remedies when applying statistics to financial time series
- Univariate time series modeling and forecasting, the concept of stationarity
- Multivariate time-series models (structural models, vector auto-regressions), multivariate stationarity
- Modelling and forecasting volatility
- Multivariate time-series models (structural models, vector auto-regressions), multivariate stationarity
Lernergebnisse
- Students understand when to use univariate end multivariate models, know how to test and implement them and can interpret the output of such models.
- Students can explain co-integration and how it relates to univariate stationarity and apply the necessary testing algorithms.
- Students understand and know how to implement models of univariate and multivariate volatility.
Kompetenzen
Lehrmethoden
Interactive lectures
Literatur
- Brooks, C. (2019). Introductory Econometrics for Finance (4th ed.). Cambridge, United Kingdom ; New York, NY: Cambridge University Press.
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: With Applications in R (1st ed.). Springer.
Prüfungsmodalitäten
see lecture(s) within the module