Module FINN2061: Programming for Finance

Department: Finance

FINN2061: Programming for Finance

Prerequisites

•  Quantitative Methods

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To introduce students to the basics of programming for finance and its applications in financial data analysis.
• To enable students to use Excel, Python, or R to manipulate, analyse, and visualize financial data.
• To provide an overview of financial calculations, modelling, and portfolio management using computational methods.
• To introduce students to the use of APIs for data collection in finance.

Content

• Introduction to programming concepts and tools for finance.
• Data collection for finance: Scraping and cleaning data using Python or R; using APIs to access financial data.
• Introduction to programming in Python and Excel: Syntax, data types, and control structures; working with financial time series data; statistical analysis and visualization of financial data.
• Financial calculations in Excel: Time value of money, compound interest, financial ratios, and other financial formulas.
• Financial modeling: Building and analyzing financial models using Excel and Python.
• Portfolio management: Mean-variance optimization, risk and return analysis, and portfolio construction using computational methods.
• Case studies and practical exercises using real-world financial data.

Learning Outcomes

• Basic knowledge of programming for finance and its applications in financial data analysis.
• Understanding of financial calculations and modeling techniques.
• Overview of portfolio management and data collection in finance.

• Ability to use Excel, Python, or R to manipulate, analyze, and visualize financial data.
• Ability to implement and evaluate basic financial models and portfolio management techniques using computational methods.
• Ability to use APIs to access financial data for analysis.

• Written communication through assignments and reports.
• Planning and organizing through project management and time management.
• Problem solving through the application of analytical and computational skills to financial data.
• Initiative through independent research and learning.
• Numeracy through the analysis and interpretation of financial data.
• Computer literacy through the use of programming languages and financial software.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures and workshops on programming concepts and tools for finance.
• Hands-on workshops and practical exercises using Excel, Python, or R to manipulate, analyze, and visualise financial data.
• A time constrained online test (Formative assignment).
• Summative assignment is via an online test undertaken during term time and a written individual assignment. The summative assessment covers both the theoretical and practical aspects of the module.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

A time constrained online test.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University