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FIN30200

Academic Year 2024/2025

Econometrics of Financial Markets (FIN30200)

Subject:
Finance
College:
Business
School:
Business
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Assoc Professor Alessia Paccagnini
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 with a comprehensive understanding of the econometric techniques used in financial economics. It explains the nature of time series econometrics and demonstrates applications in business, economics and finance. The model will cover the latest econometric tools used in analysing economic and financial time series data. Specifically we focus on issues such as: Stationarity, Cointegration and Error Correction Models, time varying volatility models and regime-switching models. Strong emphasis will be placed on the practical application of such models to real financial data.
Some computer software packages will be used to estimate models and perform diagnostic tests.

About this Module

Learning Outcomes:

At the end of this course students should be able to:
1) Apply the techniques introduced to practical problems in financial economics.
2) Understand and explain the principles underlying the main testing and modelling paradigms in econometric analysis.
3) Apply and assess the methodology of time series analysis in finance.

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 lectures' quizzes, applied projects, and video presentations.

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
Not applicable to this module.
 

Assessment Strategy Invalid Option
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Individual Project: Individual CAPM project by using Python Week 5 Alternative linear conversion grade scale 40% Yes
35
 Yes
Group Work Assignment: Replication of a research paper Week 12 Alternative linear conversion grade scale 40% Yes
20
 Yes
Assignment(Including Essay): In-class assignment on the last day Week 12 Alternative linear conversion grade scale 40% Yes
35
 Yes
Quizzes/Short Exercises: Class Partecipation Week 1, Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11, Week 12 Alternative linear conversion grade scale 40% Yes
10
 Yes

Carry forward of passed components Invalid Option
Yes
 

Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Self-assessment activities

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Martina Assereto Tutor
Miss Yumeng Gao Tutor
Diego Pérez Guisande Tutor
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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