Dr Linyan Zhu (Autumn Term)

Dr Christian Julliard (Winter Term)

This course is compulsory on the MSc in Finance and Economics and MSc in Finance and Economics (Work Placement Pathway). This course is not available as an outside option.

This course does not permit auditing students.

Mathematical background to the level of the course taught in September in the Economics Department (EC400) is assumed.

This course covers the techniques of empirical investigation in economics and finance. Students are introduced to recent empirical findings based on asset pricing and corporate finance models. The course includes a selection of the following topics: multivariate regression; maximum likelihood estimation; hypothesis testing; omitted variables and misspecification; asymptotic theory; methods for casual inference; introduction to machine learning; time-series modelling; predictability of asset returns; event study analysis; econometric tests of the CAPM and multifactor models; volatility modelling; generalised method of moments estimation; introduction to Bayesian econometrics, model selection and model averaging, and large-scale modelling.

30 hours of lectures in the AT. 33 hours of lectures in the WT.

This course is taught in the interactive lecturing format. There is no distinction between lectures and classes/seminars; there are “sessions” only, and the pedagogical approach in each session is interactive.

Exercises are provided each week and they are discussed in class.

A complete reading list is available at the beginning of session. Readings will be based on Hansen, Econometrics; Hayashi, Econometrics; Hamilton, Times Series Analysis; Greene, Econometric Analysis, Prentice-Hall; Campbell, Lo & MacKinlay, The Econometrics of Financial Markets, Princeton University Press; Econometric Analysis of Cross Section and Panel Data, J. Wooldridge; Contemporary Bayesian Econometrics and Statistics, Wiley Series in Probability and Statistics, J. Geweke; selected published articles.

Continuous assessment (100%).