The Master of Science in Quantitative Finance programme, as envisioned by the Amrut Mody School of Management at Ahmedabad University, is a unique programme in the country for it focusses on imparting advanced quantitative techniques that is required for students who are intent on pursuing a career in Financial Modelling, Asset Management, Risk Mitigation, and Investment Banking. Unlike specialised programmes that are offered in silos, the Master of Science in Quantitative Finance programme at Ahmedabad University offers ample avenues to the students to make the most out of the broader liberal arts university ecosystem that encourages and nurtures interdisciplinarity.
The Master of Science in Quantitative Finance is a fully-residential two-year post-graduate programme offered by Amrut Mody School of Management of Ahmedabad University. This programme is a confluence of mathematics, financial markets, and economics. The contents and the depth of the courses offered in this programme have been arrived at keeping in view the demands and the expectations of industry. Graduating students are expected to have a deep understanding of the mathematical underpinnings of financial markets. They should possess requisite coding skills and should be in a position to apply the quantitative techniques in real-world context to address empirical anomalies. The pedagogy consists of, not limited to, faculty led classroom discussions, simulation exercises, case analysis/group activities, workshops, and practitioner interactions.
Programme Uniqueness
Master of Science in Quantitative Finance programme is unique when compared to similar kinds of programmes offered by prestigious institutes in India and abroad in the following ways:
Master of Science in Quantitative Finance programme offers strong theoretical foundations of mathematical finance in general and financial markets in particular. The programme comprises of a set of core and elective courses with focus on computational finance. The core courses are designed to build a strong foundation for the students based on which they can choose from a diverse pool of electives matching individual interests. Along with advanced techniques in finance, the courses on economics and analytics offer the right blende for making this a unique programme.
The programme requires all students to successfully complete an internship, duration of which is between 6-8 weeks at the end of the first academic year.
Learning Outcomes
On successful completion of the Master of Science in Quantitative Finance programme, a student is expected to have both strong theoretical as well as empirical understanding of the subject. Further, the internship will expose students to applying the knowledge gained in real life and thus, build a bridge between theory and practice. As a part of the curriculum, students will also acquire proficiency in relevant programming techniques that are key ingredients for a successful future career.
Minimum Programme Credits: 80
Credits | |
---|---|
Programme Core | 25 |
TOD501 Descriptive and Inferential Statistics | 1.5 |
TOD601 ANOVA and Regression | 1.5 |
ECO501 Intermediate Microeconomics | 3 |
ECO511 Intermediate Macroeconomics | 3 |
TOD504 Mathematical Methods for Economics | 3 |
TOD531 Analytics Lab | 1 |
FAC633 Security Analysis and Portfolio Management | 3 |
FAC541 Financial Markets and Institutions | 3 |
ECO520 Econometrics | 3 |
FAC533 Corporate Investments and Value Creation | 3 |
Discipline Core | 12 |
FAC631 Derivatives and Risk Management | 3 |
FAC635 Financial Modelling | 3 |
FAC638 Fixed Income Securities | 3 |
FAC639 Modelling Randomness in Financial | 3 |
Discipline Electives | 24 |
FAC534 Strategic Corporate Finance | 3 |
FAC630 Behavioural Finance | 3 |
FAC632 Corporate Restructuring: Mergers & Acquisitions | 3 |
FAC634 International Finance | 3 |
FAC637 Business Valuation | 3 |
FAC636 Financial Econometrics | 3 |
FAC644 FinTech Ventures | 3 |
FAC643 Bank Management | 3 |
FACXXX Venture Capital and Private Equity | 3 |
FACXXX Algorithmic Trading and Market Microstructure | 3 |
Free Electives | 12 |
TOD533 Advanced Business Analytics | 3 |
ECO592 Machine Learning for Policy | 3 |
ECO502 Introduction to Game Theory | 3 |
ECO620 Empirical Methods in Economics | 3 |
CSE523 Machine Learning | 3 |
MGT508 Sustainability, Business and Society | 3 |
MGT534 Corporate Governance | 1.5 |
Skill Building Foundation Modules | 4 |
Managerial Communication | 1.5 |
Python for Finance | 1.5 |
Math Tutorials | 1 |
Summer Internship | 3 |
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