Dr Christian Julliard

This course is available on the CEMS Exchange, MBA Exchange, MSc in Accounting and Finance, MSc in Finance and Economics, MSc in Finance and Private Equity, MSc in Financial Mathematics, MSc in Quantitative Methods for Risk Management, MSc in Risk and Finance, MSc in Statistics (Financial Statistics) and MSc in Statistics (Financial Statistics) (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.

Students must have completed Quantitative Methods for Finance and Risk Analysis (FM442).

The first half of FM437 Financial Econometrics, or alternatively FM442 Quantitative Methods for Finance and Risk Analysis, is a required prerequisite. Students who can demonstrate comparable background may be granted an exemption from this requirement.

This course will examine the techniques involved with forecasting key variables in finance, and how to incorporate model uncertainty into financial forecasts. Students will learn both the theory and the practice of forecasting in finance.

The following topics will be covered: introduction to time series analysis; Maximum Likelihood Estimation (MLE) with time series data, and MLE based model selection; Bayesian inference, posterior probabilities, and Bayesian Model Averaging; Markov Chain Monte Carlo methods; present value regressions, vector autoregressios, causality, and cointegration; asset pricing and the Generalized Method of Moments (GMM); frequentist and Bayesian information theoretic alternatives to GMM.

Additional information can be found on Moodle (for current students)

20 hours of lectures, 10 hours of classes and 10 hours of computer workshops in the LT.

Regular problem sets.

Lecture notes will be provided, and some journal articles may also be used.

Exam (100%, duration: 3 hours and 15 minutes) in the main exam period.