FIN3009S Data Analytics for Finance

Academic Year 2023/2024

This module covers the fundamental mathematical and statistical background necessary for the understanding of financial markets. The aim of this module is to examine why and how Finance professionals use data and quantitative methods. A comprehensive range of quantitative techniques are reviewed, however the main focus is on applications in Finance. The first part of the module will introduce students to the basic techniques of data analysis used by Finance professionals. This will include a discussion of the main databases, a review of the key features of market data, as well as the techniques available for analysing this data. In order to develop a comprehensive understanding of financial analysis we examine a number of key quantitative principles in the second part. Key relationships will be examined including discounting and the time value of money. The module is concluded with an introduction to empirical relationships in Finance using econometric analysis.

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Curricular information is subject to change

Learning Outcomes:

Learning Outcomes
1. Demonstrate knowledge and understanding of the key elements of financial analytics.
2. Apply quantitative techniques to practical real world problems in finance and business.
3. Implement a range of analytical metrics in an efficient manner using spreadsheets.
4. Develop research skills including data analysis.

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities


Autonomous Student Learning






Approaches to Teaching and Learning:
Students will attend classes for this module and have the opportunity to engage in active learning during these sessions. There will be in-class discussion and group work to analyse module concepts. Where appropriate, the module will incorporate case based learning. 
Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Online end of trimester assessment Coursework (End of Trimester) n/a Graded No


Group Project: Group Project - Empirical (Excel) Varies over the Trimester n/a Graded No


Carry forward of passed components
Remediation Type Remediation Timing
Repeat Within Two Trimesters
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

General feedback is provided to students on all their submitted assessment components.

Name Role
Dr Vassilios Papavassiliou Lecturer / Co-Lecturer
Dr Christina Burke Tutor
Ms Michele Connolly Tutor
Dr Kevin (Yong Kyu) Gam Tutor
Richa Gupta Tutor
Shirley Ho Tutor
Rachel Sim Tutor
Dr Anita Suurlaht Tutor
Chee Shong Tan Tutor
Charlene Tan Puay Koon Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.

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