Interdisciplinary Dual Degree (IDDD) - MS (Quantitative Finance)
Objectives Of The Program
- Enable students to more easily adapt to new developments in finance and bridge the gap between application of modern product and process technologies and state-of-the-art finance.
- Build advanced knowledge of the main theoretical and applied concepts in quantitative finance, financial engineering and risk management, using current issues to stimulate the thinking process.
- Prepare for careers involving the design and management of new financial instruments, the development of innovative methods for measuring, or predicting and managing risk.
Eligibility
- Open to all branches of IITM
- Minimum CGPA of 8.0 at the end of 5th semester.
- Selection will be strictly based on CGPA till the 5th semester.
Credit Requirements
- Core: 60 credits
- Elective: 30 credits
- Project: 70 credits: Earned over the 9th and 10th semesters plus the summer preceding or succeeding them. Can be done in collaboration with industry.
Course Categories
- Fundamental Finance – To understand the core principles, theories and concepts of finance
- Advanced financial tools and techniques – To understand the current state-of-the art in the financial markets. Particular focus on the new innovations in fintech.
- Computational/Analytical capabilities – To acquire analytical skills in the context of finance.
Course Curriculum
|
Sr # |
Course # |
Course name |
L |
T |
E |
P |
O |
C |
|---|---|---|---|---|---|---|---|---|
|
Semester 6 |
Jan – May |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
MS6621(New) |
Corporate Finance |
4 |
0 |
0 |
0 |
8 |
12 |
|
|
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|
Semester 7 |
July – Nov |
|
|
|
|
|
|
|
|
1 |
HS5701 |
Microeconomics -I (if not credited earlier) |
3 |
0 |
0 |
0 |
6 |
9 |
|
2 |
MA5015 |
Stochastic Calculus for Finance |
3 |
0 |
0 |
0 |
6 |
9 |
|
3 |
IDxxx(New) |
Introduction to Machine learning |
4 |
0 |
0 |
0 |
8 |
12 |
|
|
||||||||
|
Semester 8 |
Jan – May |
|
|
|
|
|
|
|
|
1 |
MA 5950 |
Mathematical Finance |
3 |
0 |
0 |
0 |
6 |
9 |
|
2 |
MSXXX(new) |
Financial Derivatives and Markets |
4 |
0 |
0 |
0 |
6 |
9 |
|
3 |
MS XXX |
Multivariate analysis –elective 1 |
4 |
0 |
0 |
0 |
8 |
12 |
|
|
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|
Summer |
|
|
|
|
|
|
|
|
|
1 |
Xxx |
Project – Phase 1 |
0 |
0 |
0 |
0 |
0 |
15 |
|
|
|
|||||||
|
Semester 9 |
July – Nov |
|
|
|
|
|
|
|
|
1 |
xxx |
Elective 2 |
4 |
0 |
0 |
0 |
8 |
6 |
|
2 |
xxx |
Elective 3 |
4 |
0 |
0 |
0 |
8 |
6 |
|
3 |
xxx |
Elective 4 |
4 |
0 |
0 |
0 |
8 |
6 |
|
4 |
xxx |
Project – Phase 2 |
0 |
0 |
0 |
0 |
0 |
20 |
|
|
||||||||
|
Semester 10 |
Jan – May |
|
|
|
|
|
|
|
|
1 |
xxx |
Project – Phase 3 |
0 |
0 |
0 |
0 |
0 |
35 |
|
|
||||||||
Note: Students are requested to do the HS3002 Principles of Economics (if not credited earlier) either in the sixth or eight quarter
DoMS Electives
- Asset Pricing (MS5617) – 6 credits
- Fixed Income Securities, Structure and Trading (MS6680) – 6 credits
- Financial Risk Management (MS6710) – 6 credits
- Computational Finance (MS5690) – 6 credits
- Venture Capital and Entrepreneurial Finance (MS6640)- – 6 credits
- FinTech and Entrepreneurship [New elective] – 6 credits
- Algorithmic Trading [New elective]- – 6 credits
- Valuation and Investment Banking
IDDD electives
- Machine Learning and Data Science for Finance [New elective]-12 credits
- Time Series Modelling for Finance [New Elective]- 12 credits
- Block Chain technology and Crypto currency [New Elective]- 12 credits
- Deep learning Techniques [New Elective]- 12 credits