MASTER OF TECHNOLOGY IN FINANCIAL ENGINEERING
MASTER OF TECHNOLOGY IN FINANCIAL ENGINEERING
The Master of Technology Degree in Financial Engineering seeks to further advance knowledge and skills in the design, development and implementation of innovative financial instruments and processes in solving challenges in finance. Financial Engineering’s growth as a discipline has been fuelled by an active corporate community with asset management companies, insurance companies, and some advanced corporate treasury departments leading the pack. Long-term outlooks in the financial services industry suggest a trend toward ever more quantitative analysis and methods. The development and creative application of financial theory and financial instruments is thus key in structuring solutions to complex financial challenges and to exploit financial opportunities; given the dynamic environment that characterizes today’s financial services industry. The programme is designed to provide a broad understanding in the application of engineering methodologies and quantitative methods to finance through equipping students with in-depth operational skills in the design, analysis and construction of financial solutions to meet the needs of enterprises/economies.
Intended Learning Outcomes (ILO)
Upon completion of the programme, graduates must be able to develop;
- Innovative financial solutions that meet the needs of enterprises and economies both locally and internationally.
- Knowledge of theoretical and practical understanding in the formulation, implementation, and evaluation of financial models and systems.
- Modern financial instruments for use in the financial markets.
- Advanced techniques for use financial engineering i.e. data analytics, product structuring, programming, numerical analysis, statistics, financial economics, risk management, corporate financial engineering, and investment management strategies.
- Create employment through application of acquired technopreneurial skills
1.1.1.1.1 Programme Structure
Course Code | Course Narration | Directed Learning | Self-Study Time | Scheduled Assessment | L-T-P | Total | Credits |
BFE7101 | Advanced Financial Econometrics | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
BFE7102 | Stochastic Calculus for Finance | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
BFE7103 | Global Financial Markets | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE7104 | Lab I: Data Analysis for Financial Engineering | 46 | 94 | 20 | 0-0-4 | 160 | 16 |
Electives (choose one) | |||||||
BFE7105 | Fixed Income Securities and Interest Rate Modelling | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE7106 | Actuarial Models | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE7107 | Investment Banking | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
Total |
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| 800 | 80 |
Course Code | Course Narration | Directed Learning | Self-Study Time | Scheduled Assessment | L-T-P | Total | Credits |
BFE7201 | Quantitative Risk Management | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE7202 | Numerical Analysis in Finance | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
BFE7203 | Computational Methods in Derivatives Pricing | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
BFE7204 | Lab II: Financial Analytics and Big Data in Finance | 46 | 94 | 20 | 0-0-4 | 160 | 16 |
BFE7205 | Research Methodology | 48 | 96 | 16 | 2-0-2 | 64 | 16 |
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Electives(Choose one) | |||||||
BFE7206 | Credit Risk Modelling | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE7207 | Advanced Corporate Financial Engineering | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE7208 | Behavioural finance | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
Total |
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| 840 | 96 |
Course Code | Course Narration | Directed Learning | Self-Study Time | Scheduled Assessment | L-T-P | Total | Credits |
BFE8101 | Advanced Portfolio Engineering | 48 | 96 | 16 | 2-2-0 | 160 | 16 |
BFE8102 | Optimization Models and Methods in Finance | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
BFE8103 | Advanced Object Oriented Programming in Financial Engineering | 48 | 96 | 16 | 2-0-2 | 160 | 16 |
BFE8104 | Seminar | 6 | 14 | 20 | 2-0-2 | 40 | 4 |
HIT800 | M-Tech Dissertation -Phase I | 20 | 840 | 40 | 0-0-40 | 300 | 30 |
Total |
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| 1444 | 82 |
Course Code | Course Narration | Directed Learning | Self-Study Time | Scheduled Assessment | L-T-P | Total | Credits |
HIT 800 | M-Tech Dissertation -Phase II | 20 | 840 | 40 | 0-0-40 | 900 | 60 |