IC208: Programming for Finance

IC208: Programming for Finance

Module code: IC208

Module provider: ICMA Centre; Henley Business School

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 2

Module convenor: Dr Vu Tran, email:


Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: No

Last updated: 28 May 2024


Module aims and purpose

This module introduces students to Object Oriented Programming using Python as the main programming language and its applications in Finance. Programming skills are among the most desired in today data driven business landscape. The module aims to present topics such as the basics of programming, including class, objects, datatypes, conditional statements and loops, processing data from files, receiving inputs and displaying relevant outputs. Students who complete this course should be able to write simple programming functions in Python, process data files including reading, and modifying and writing data to external files, data management and visualisation. In additional, students will learn to read and write to Excel and CSV files, connect to databases, obtain and process data from the Web, as well as use Python for Finance and Econometrics.

Module learning outcomes

By the end of the module, it is expected that students will be able to:

  1. Demonstrate an appropriate academic knowledge of the fundamental concepts in Python programming and its applications in Finance such as Investments, and econometrics;
  2. Analyse and handle datasets from various online platforms such as World Bank, Thomson Reuter, social media datasets and others;
  3. Apply team-working skills and appreciate the value of diversity and multiculturalism via the module group project;
  4. Apply and evaluate leading-edge practices in finance.

Module content

  1. Introduction to programming with Python
  2. Class, Object, Variables, Datatypes
  3. Conditional Statements, Loops and writing functions in Python
  4. Important Python libraries including Numpy, Pandas
  5. Pandas for data management
  6. Data visualisation
  7. Python I/O, interacting with the OS system, reading/writing from/to files
  8. Using Python to connect to databases including connections to the Web
  9. Using Python for applications in Finance/Econometrics


Teaching and learning methods

Lectures will combine theoretical frameworks as well as the practical aspects of Python programming and relevant applications. Students will directly apply what they are being taught during seminars. In-person teaching will be supplemented with digital learning such as discussion boards, polling and video recordings.

This module may be taught in a different Semester if you are studying at our campus in Malaysia.

For students studying at our campus in Malaysia: This module may be taught in a different semester and the breakdown of study hours may differ to those set out in the Study Hours table (please refer to the Module Handbook for the correct breakdown). In addition, you will be required to complete an additional 40 hours of study, taking the total number of study hours to 240 for this module. This is to comply with the Malaysian Quality Agency (MQA).

Study hours

At least 30 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

 Scheduled teaching and learning activities  Semester 1  Semester 2  Summer
Lectures 20
Seminars 10
Project Supervision
Practical classes and workshops
Supervised time in studio / workshop
Scheduled revision sessions
Feedback meetings with staff
External visits
Work-based learning

 Self-scheduled teaching and learning activities  Semester 1  Semester 2  Summer
Directed viewing of video materials/screencasts 10
Participation in discussion boards/other discussions 10
Feedback meetings with staff
Other 5
Other (details)

 Placement and study abroad  Semester 1  Semester 2  Summer
Study abroad

Please note that the hours listed above are for guidance purposes only.

 Independent study hours  Semester 1  Semester 2  Summer
Independent study hours 145

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.


Requirements for a pass

In order to pass, students need to obtain a mark of 40% or more.

Summative assessment

Type of assessment Detail of assessment % contribution towards module mark Size of assessment Submission date Additional information
In-class test administered by School/Dept In-Class test 40 1hour Week 5, Semester 2 This test combines multiple choice questions and coding challenges
Written coursework assignment Group Project 60 2,000 words Assessment week 2-3, Semester 2 Group project; marks will be based on both the final project and individual contributions.

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
  • the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
  • where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
  • where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

  • where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
  • where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at:

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.


Type of reassessment Detail of reassessment % contribution towards module mark Size of reassessment Submission date Additional information
Written coursework assignment Individual Project 100 2,000 words During the University resit period Individual Project

Additional costs

Item Additional information Cost
Computers and devices with a particular specification
Printing and binding
Required textbooks
Specialist clothing, footwear, or headgear
Specialist equipment or materials
Travel, accommodation, and subsistence


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