Dr Christian Julliard, OLD M2.18

Intended for students on the MSc Finance and Economics, MSc Finance and Economics (Research), MSc Financial Mathematics, MSc Accounting and Finance, MSc Statistics (Financial Statistics), MSc Statistics (Financial Statistics) (Research), MSc Management and Regulation of Risk and MSc Risk and Finance.

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 Christian Julliard's teaching page and on On Moodle (for current students)

Teaching: 30 hours of combined lectures/classes in the LT.

Regular problem sets.

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

A three-hour written examination (plus 15 minutes reading time) in the ST (100%).