Financial Econometrics for Research Students

This information is for the 2016/17 session.

Teacher responsible

Dr Andrea Tamoni, Professor Raffaella Giacomini and Professor Denis Kristensen


This course is compulsory on the MRes/PhD in Finance (Route 1) and MSc in Finance and Economics (Research). This course is available on the MPhil/PhD in Accounting. This course is available as an outside option to students on other programmes where regulations permit.

Optional on MRes/PhD Economics.


Strong background in statistics and mathematics; some knowledge of Economics and Finance.

Course content

The Lent Term of FM481 is shared with FM404 Forecasting Financial Time Series.

Part 1 – Probability, Mathematical Statistics, and Asymptotic Theory, provides students with an understanding of basic concepts in probability and statistics with a view of eventual use for econometric analysis of financial data. Including Basic Probability Concepts, Random Variables, Selected Probability Distributions, Modes of Convergence, Properties of Estimators, Frequentist Hypothesis Testing and Bayesian Inference.

Part 2 - Theory and application of regression analysis, covers estimation and inference theory for regression models. The topics covered are least squares estimation, maximum likelihood estimation, instrumental variable estimation, and generalized method of moments estimation, with applications to linear models, many and weak instrument problems, limited dependent variable models, and panel data models.

Part 3 - The course provides a survey of the theory and application of time series methods in econometrics. . The main objective of this course is to develop the skills needed to do empirical research in fields operating with time series data sets. The topics covered are: Hilbert spaces, projections, Wold theorems, ARMA models, Z-transform, convolution theorem, W-K prediction, Spectral analysis, VARs, unit roots; State Space Representations; Models with time-varying coefficients and stochastic volatility; Nonlinear filtering (particle filters); Predictability.


20 hours of lectures in the MT. 36 hours of lectures in the LT.

Formative coursework

Weekly classwork and problem sets.

Indicative reading

• Cameron and Trivedi: Microeconometrics. Methods and Applications.

• Campbell, Lo and MacKinlay: The Econometrics of Financial Markets

• Geweke: Contemporary Bayesian Econometrics and Statistics

• Gourieroux and Jasiak: Financial Econometrics: Problems, Models and Methods.

• Greene: Econometric Analysis.

• Johannes and Polson: Computational Methods for Bayesian Inference.

• Hamilton: Time-Series Analysis.

• Hayashi: Econometrics

• Roberts and Whited: “Endogeneity in Empirical Corporate Finance,” Handbook of the Economics of Finance, vol. 2.

• Sargent, T., (1987), Macroeconomic Theory, chapters IX-XI.

• Wooldridge: Econometric Analysis of Cross-Section and Panel Data.


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

Key facts

Department: Finance

Total students 2015/16: 13

Average class size 2015/16: 13

Controlled access 2015/16: Yes

Value: One Unit

Guidelines for interpreting course guide information

Personal development skills

  • Application of numeracy skills
  • Specialist skills