M.Sc :
The programme shall be of two years duration and shall consist of six terms each having at least sixty teaching days.
Course Structure :
1st Year
Term 1
Course No. | Course Title | No.of Lectures | Practical | Credit |
---|---|---|---|---|
111 | Introduction to probability | 3 | 0 | 3 |
112 | Mathematical Foundatio | 4 | 0 | 4 |
113 | Foundation of Finance | 6 | 0 | 6 |
114 | Programming in C++ | 3 | 4 | 5 |
Term 2
Course No. | Course Title | No.of Lectures | Practical | Credit |
---|---|---|---|---|
121 | Stochastic Process and Inference | 3 | 0 | 3 |
122 | Numerical Analysis | 3 | 2 | 4 |
123 | Financial Derivatives | 3 | 0 | 3 |
124 | Corporate Finance | 3 | 0 | 3 |
125 | Object Oriented Programming in C ++ | 2 | 4 | 3 |
126 | Financial Modeling using excel | 0 | 4 | 2 |
Term 3
Course No. | Course Title | No.of Lectures | Practical | Credit |
---|---|---|---|---|
131 | Numerical Solution of Differential Equations. | 3 | 2 | 4 |
132 | Computational modeling of Financial derivatives | 3 | 2 | 4 |
133 | Financial risk Management and measurement | 3 | 2 | 4 |
134 | Stochastic Processes in Finance | 3 | 0 | 3 |
135 | Financial accounting and Regulation | 3 | 0 | 3 |
Summer Training of at least Four Weeks duration.
2nd Year
Term 4
Course No. | Course Title | No.of Lectures | Practical | Credit |
---|---|---|---|---|
211 | Fixed Income security models | 2 | 2 | 3 |
212 | Credit derivative pricing model | 3 | 2 | 4 |
213 | Elective 1 | 3 | 0 | 3 |
214 | Elective 2 | 3 | 0 | 3 |
215 | Elective 3 | 3 | 0 | 3 |
Term 5
Course No. | Course Title | No.of Lectures | Practical | Credit |
---|---|---|---|---|
221 | Financial product design: Principles and case studies | 2 | 2 | 4 |
222 | Elective 4 | 3 | 0 | 3 |
223 | Elective 5 | 3 | 0 | 3 |
224 | Dissertation Preparatory Part | 6 |
Term 6
Course No. | Course Title | No.of Lectures | Practical | Credit |
---|---|---|---|---|
231 | Dissertation Final Part | 0 | 0 | 10 |
Courses for Electives 1, 2, 4 shall be chosen from the following :
- Fundamentals of actuarial science I
- Fundamentals of actuarial science II
- Time series Analysis and forecasting
- Quantitative risk management
- Advanced topics in financial derivatives
- Dynamic asset management
- Optimization in Finance
- Monte-Carlo Methods in Financial Engineering
Courses for Electives 3, 5
- Soft computing methods in Finance
- Parallel computing
- Artificial intelligence and machine learning
- Objected Oriented software engineering.