FIN41660 Financial Econometrics

Academic Year 2023/2024

This course aims to provide students with a broad understanding of the discipline of econometrics
for finance, from an ab initio vantage point. It endeavours to explain the nature of financial econometrics and to provide illustrative applications in business, economics and finance. In particular,
this course focuses on the classic linear regression model, the assumptions of that model and several
diagnostic tests to examine same. The course derives and discusses the Ordinary Least Squares
estimation technique. It also introduces alternative estimation methodologies, namely a number of
Least Squares variants, the Maximum Likelihood Estimator and the Generalized Method of Moments Estimator. Finally, several non-linear type regression models are considered.
The MATLAB computer software package will be used to estimate models and perform diagnostic tests.

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Curricular information is subject to change

Learning Outcomes:

At the end of this course students should:
1) have knowledge as well as an understanding of the essential components of introductory and
intermediate level econometrics;
2) be able to apply econometric techniques to address important questions in business, economics
and finance;
3) have developed a "healthy" skepticism towards econometric models and their estimation based
on a sensible consideration of the data and techniques employed;
4) have had the opportunity to practice problem solving and improve their analytical skills.

Student Effort Type Hours
Lectures

90

Small Group

1

Tutorial

30

Total

121

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Incompatibles:
ECON42710 - Adv Metrics: Time Series


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Continuous Assessment: Online homework and quizzes Throughout the Trimester n/a Graded Yes

70

Examination: Online Final Exam 2 hour End of Trimester Exam Yes Graded Yes

30


Carry forward of passed components
Not yet recorded
 
Resit In Terminal Exam
Spring No
Not yet recorded
Name Role
Ms Sinian Zheng Tutor
Mingchuan Zhou Tutor
Autumn
     
Lecture Offering 1 Week(s) - 7 Fri 13:30 - 15:20
Tutorial Offering 1 Week(s) - 8, 9, 10, 11, 12 Fri 14:30 - 15:20
Lecture Offering 1 Week(s) - 9, 10, 11, 12, 13 Mon 16:00 - 17:50
Workshop Offering 1 Week(s) - 9 Mon 18:30 - 20:00
Lecture Offering 1 Week(s) - 7, 8, 9, 10, 12 Thurs 13:30 - 15:20
Lecture Offering 1 Week(s) - 10 Wed 12:00 - 13:50
Online Learning Offering 1 Week(s) - 12 Wed 12:00 - 13:50
Tutorial Offering 2 Week(s) - 8, 9, 10, 11, 12 Fri 13:30 - 14:20
Lecture Offering 2 Week(s) - 7 Fri 13:30 - 15:20
Lecture Offering 2 Week(s) - 9, 10, 11, 12, 13 Mon 13:30 - 15:20
Lecture Offering 2 Week(s) - 7, 8, 9, 10, 12 Thurs 16:00 - 17:50
Lecture Offering 2 Week(s) - 10 Wed 12:00 - 13:50
Online Learning Offering 2 Week(s) - 12 Wed 12:00 - 13:50
Autumn
     

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