Principles of Financial Modelling and Programming
| Code | School | Level | Credits | Semesters |
| BUSI2198 | Nottingham University Business School China | 2 | 10 | Autumn China |
- Code
- BUSI2198
- School
- Nottingham University Business School China
- Level
- 2
- Credits
- 10
- Semesters
- Autumn China
Summary
REQUISITES
Please note that for this module, the following pre-requisite applies:
BUSI1074 Quantitative Method 1b
BUSI1070 Business Finance
The following co-requisite applies:
BUSI2105 Quantitative Method 2A
The following anti-requisite applies:
BUSI2189 Introduction to Business Programming
(Please ignore Requisites: N/A below)
This module builds upon the foundational knowledge of Finance by introducing a hands-on approach to the practical application of financial theory. Through mathematical modelling and computational programming, students will learn to use real-world financial data to model the returns and risks of financial assets. Students are then expected to construct and optimize investment portfolios, and implement corresponding investment strategies in response to evolving economic and financial landscapes. This will equip them with a robust toolkit of skills, bridging the gap between finance theory and practical financial modelling. Overall, this module provides students with a comprehensive understanding of financial modelling principles, programming fundamentals, and financial data analysis techniques.
Re-assessment format is decided by the school.
Target Students
Part I Business School students
Classes
- One 1-hour seminar each week for 4 weeks
- One 2-hour lecture each week for 11 weeks
Assessment
- 30% Group Coursework 1
- 70% Exam 1 (1-hour-30-minute)
Assessed by end of autumn semester
Educational Aims
The aim of this module is to provide students with a comprehensive understanding of financial modelling principles. This module seeks to equip students with the proficiency to utilize prevalent programming languages for financial data analysis and to implement different financial models. The module also aims to help students better understand how the mathematical theories are applied in financial modelling. The ultimate goal is to enable students to apply theoretical finance and mathematical modelling concepts to real-world financial data, thereby enhancing their decision-making skills in investment management and risk mitigation.Learning Outcomes
- Apply financial modelling techniques to accurately model asset risk and return, and explore various approaches to constructing investment portfolios.
- Calibrate and validate financial models using real-world financial data and using prevalent programming languages.
- Write clean, efficient, and well-documented code in computational programming.
- Refine, optimize, and backtest investment strategies, ensuring they are robust and adaptable through the use of critical thinking and analytical skills
- Evaluate assumptions, interpret data-driven insights, and make informed adjustments to strategies in response to evolving economic and financial landscapes, considering their relative advantages and disadvantages.
- Assess the effectiveness of investment portfolios by rigorously balancing risk against performance to meet predefined investment objectives.
- Assess and enhance portfolio robustness, customizing strategies to accommodate different risk tolerance levels and investment horizons, using statistical measures and risk-adjusted performance metrics.
- Work collaboratively with an awareness of mutual interdependence.
Conveners
- Mr Tianlun Fei