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FIN30200

Academic Year 2025/2026

Econometrics of Financial Markets (FIN30200)

Subject:
Finance
College:
Business
School:
Business
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Dr Iason Kynigakis
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This module aims to provide students a solid understanding of the econometric approaches that are commonly employed in finance and economics from an applied perspective. In particular, the module begins with an overview of the classical linear regression model, the ordinary least squares (OLS) estimator, progressing to hypothesis testing and model diagnostics. The module then covers univariate time series modelling, including ARMA processes, forecasting and explores the topics of stationarity and cointegration. It further introduces volatility modelling with ARCH and GARCH frameworks. Real-world data will be used throughout to demonstrate applications and to answer empirical questions in finance.

About this Module

Learning Outcomes:

On completing this module, students will be able to:
• Estimate and interpret linear regression models using OLS.
• Conduct diagnostic tests, identify model violations, and apply corrective measures.
• Specify, estimate, and evaluate univariate time series models.
• Become familiar with the concepts of stationarity and cointegration.
• Model and forecast volatility using ARCH/GARCH-type models.
• Apply econometric methods in Python to analyse and interpret real-world financial datasets.

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Tutorial

10
Autonomous Student Learning

90
Total

124

Approaches to Teaching and Learning:
Students will be involved in active learning based on quizzes, individual and group projects.

Requirements, Exclusions and Recommendations
Learning Recommendations:

Student should have an understanding of the basic concepts in statistics, inference analysis, and matrix operations.


Module Requisites and Incompatibles
Incompatibles:
ECON30540 - Advd Econometrics: Time Series


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Group Work Assignment: Group project on time series analysis Week 12 Standard conversion grade scale 40% No
20
 No
Individual Project: Individual project on linear regression Week 6 Standard conversion grade scale 40% No
35
 No
Quizzes/Short Exercises: Class participation Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11 Standard conversion grade scale 40% No
10
 No
Exam (In-person): 2-hour end of trimester exam End of trimester
Duration:
2 hr(s)
 Standard conversion grade scale 40% No
35
 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Required Readings:
Brooks, C. (2019), Introductory Econometrics for Finance, 4th Edition. Cambridge University Press

Other Readings:
Wooldridge, J. M. (2019). Introductory Econometrics a Modern Approach, 7th Edition. South-Western Cengage Learning.
Spanos, A. (2019). Probability theory and statistical inference: Empirical Modeling with Observational Data. Cambridge University Press.
Tsay, R. S. (2011). Analysis of Financial Time Series, 3rd Edition. John Wiley & Sons.
Enders, W. (2014). Applied Econometric Time Series, 4th Edition. John Wiley & Sons.

Name Role
Dr Iason Kynigakis Lecturer / Co-Lecturer
Mingchuan Zhou Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Tues 14:00 - 15:50
Autumn Tutorial Offering 1 Week(s) - Autumn: All Weeks Fri 11:00 - 11:50
Autumn Tutorial Offering 2 Week(s) - Autumn: All Weeks Fri 12:00 - 12:50
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