Not available in 2021/22
Financial Econometrics for Research Students
This information is for the 2021/22 session.
Dr Christian Julliard
Prof Alexey Onatskiy
This course is compulsory on the MRes/PhD in Finance. 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.
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; Structural VAR Models; State Space Representations; Models with time-varying coefficients and stochastic volatility; Nonlinear filtering (particle filters); Unit Roots, Spurious Regressions and Cointegration; Predictability.
22 hours of lectures in the MT. 22 hours of lectures in the LT.
Weekly classwork and problem sets.
• 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, reading time: 15 minutes) in the summer exam period.
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Important information in response to COVID-19
Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Total students 2020/21: Unavailable
Average class size 2020/21: Unavailable
Controlled access 2020/21: No
Value: One Unit
Personal development skills
- Application of numeracy skills
- Specialist skills