5010580: C20 Econometrics

Description

• 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

Learning Outcomes

• 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.

Lectures Method

Interactive lectures

Literature

• 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.