5210580: C20 Econometrics

Description

• Students will study the concepts of regression and classification problems (supervised learning) as well as principal components and clustering (unsupervised learning).
• In parallel, they will learn how to work with financial data with all its pitfalls, cover univariate and multivariate time series models of the mean and volatility and correlations, as well as model long-run relationships.

Learning Outcomes

• Students understand and can apply simple and multiple linear regressions as well as corresponding diagnostic tests.
• Students understand the pitfalls related to financial time series and know the corresponding methods and tools to overcome them.
• Students understand the concepts of supervised and unsupervised learning, can give examples and apply such methods to financial datasets.
• Students understand when to use univariate end multivariate time series 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

Lecture