37757 - Statistical Methods for Asset Management

Learning outcomes

The aim of the course is to provide the basis for modeling and statistical analysis of financial data. By the end of the course the student should be able to apply non-linear models, such as GARCH and extensions, including dynamic conditional score models, to estimate and test the capital asset pricing models, to portfolio selection problems or to estimate the value at risk. Attention will be given also to non-parametric methods.

Course contents

Introduction to statistical methods for asset management. Review of linear time series analysis. From data to models: stylised facts, volatility modelling, risk management. Nonlinear time series analysis: GARCH models, Score Driven models, extension. 

Readings/Bibliography

Textbook

Franke J., Hardle W.K., Hafner C.M. (2011), Statistics of Financial Markets, Springer (third edition)

Further reference

Harvey, A.C. (2013) Dynamic Models for Volatility and Heavy Tails, with Applications to Financial and Economic Time Series, Cambridge University Press.

Teaching methods

Lectures in person, online lectures, exercises, laboratory.

Assessment methods

Written exam, 2 hour-length, closed-books.

Students may choose to present a group project that will be assessed. In this case, the final grade will be the weighted average of the grade in the group project (50%) and of the written exam (50%).

The exam will be a pass if the final grade is greater or equal than 18.

Range of grades:

18-21 sufficient knowledge of the topics of the course

21-24 discrete knowledge of the topics of the course

24-27 good knowledge of the topics of the course

27-30 excellent knowledge of the topics of the course

Teaching tools

Textbook, lecture notes, slides and auxiliary materials that can be found on the institutional teacher web-site and in Virtuale.

Office hours

See the website of Alessandra Luati