MS Quantitative Finance at Amrut Mody School of Management, Ahmedabad University, Ahmedabad Offline Course

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

Programme Structure and Learning Pathways 

Pre-Term (Mandatory): A focused preparatory phase that ensures mathematical and computational readiness. The pre-term includes multivariate calculus, linear algebra, differential equations, probability and statistics, Python programming, modelling with R, and technical communication. Students are also introduced to Bloomberg and key financial data platforms. 

Core Courses: The core curriculum builds strong analytical depth across mathematics, statistics, economics, computer science, and finance. Students study stochastic calculus, econometrics, optimisation, asset pricing, corporate finance, derivatives and risk management, fixed income modelling, financial markets, and AI and machine learning applications in finance. Courses are sequenced to integrate mathematical theory, computational implementation, and financial decision-making. 

Electives: Students choose advanced electives to deepen specialisation in areas such as financial engineering, credit derivatives, structured products, big data analytics, text analytics, non-linear dynamics, and advanced statistics. Electives allow focused pathways in quantitative modelling, risk analytics, algorithmic strategies, and data-driven finance.

Immersive Skill Workshop: Applied workshops provide hands-on training in Bloomberg analytics, R, Matlab, SQL, Python-based portfolio optimisation, blockchain and decentralised finance modelling, and generative AI for financial analysis and reporting. 

Summer Internship: A mandatory summer internship enables students to apply quantitative tools in live industry settings across investment banking, asset management, fintech, consulting, and financial research. 

Master’s Capstone Project: In the final year, students undertake a supervised capstone project that integrates mathematical modelling, computation, and financial analysis through original research or applied industry problem-solving.  

Fees, Financial Aid: The two-year tuition fee for the incoming class of 2026 is INR 14,00,000. • 

The Tuition Fee will be payable in two equal installments (Monsoon and Winter Semester) every year, payable in advance at the beginning of each semester. 

• The student may expect to spend INR 10,000 per annum towards books and course materials. 

• Charges for participating in the Independent Study Period, Summer Semester, Immersions, and other additional services/offering to be collected separately.

Financial Aid 

▪ Teaching Assistantships are available on the basis of merit. It provides a waiver of INR 1.25 lakh per year towards the tuition fee. Teaching Assistants are required to assist faculty members in the teaching of assigned courses both semesters. Continuation of this assistantship in the second year is contingent upon maintaining a satisfactory academic performance