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Module ASB-4408:
Financial Econometrics

Module Facts

Run by Bangor Business School

15 Credits or 7.5 ECTS Credits

Semester 2

Organiser: Prof Yener Altunbas

Overall aims and purpose

To provide advanced coverage of econometric methods and practices that are used to model financial and business data, and to develop a critical awareness of the strengths and limitations of modelling techniques.

Course content

• Review of the linear regression model: estimation and hypothesis testing; • Dynamic regression models: distributed lag and autoregressive models; • Non-stationarity and testing for unit roots; • Modelling long-run relationships: cointegration; • Modelling volatility: univariate ARCH and GARCH models; • Regression analysis using panel data.

Assessment Criteria


A basic knowledge of course material.


In addition to the above, an ability to formulate, test and apply simple econometric models to relevant financial or business data sets.


In addition to the above, an ability to critically analyse the strengths and limitations of existing econometric methods using relevant theoretical and practical criteria.

Learning outcomes

  1. Demonstrate an understanding of the key theoretical underpinnings and practical applications of econometrics for financial and business analysts.

  2. Design, estimate and evaluate econometric models to financial and business data sets using the Stata econometrics software package.

  3. Demonstrate a critical awareness of the implicit assumptions and the limitations underlying empirical models based on financial and business data.

  4. Demonstrate an understanding of recent developments in time series econometrics, and their implications for modelling the returns and volatility of financial assets.

  5. Critically evaluate academic literature with an empirical content in economics, finance and business.

Assessment Methods

Type Name Description Weight
Coursework 25
Final Examination Mark 75

Teaching and Learning Strategy


Two hours of lectures per week.


One 1-hour computer workshop per week.


Courses including this module

Compulsory in courses:

Optional in courses: