QuantFin Hub @ Ashoka

A comprehensive quant finance resource featuring advanced courses and materials in mathematical finance, stochastic calculus, and quantitative methods. Developed under the Safexpress Center for Data, Learning, and Decision Sciences (SCDLDS) at Ashoka University, led by Prof. Sandeep Juneja.

Introduction to Quantitative Finance

First course in the QuantFin sequence. Featuring curated readings, lecture notes, and assignments.

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Stochastic Calculus & Mathematical Finance

Advanced course with lectures on stochastic processes, Itô calculus, and no-arbitrage pricing theory.

exSPLOre

Guest Lectures from experts on explorations in Statistics, Probability, Learning and Optimization Research.

Introduction to Quantitative Finance

This course is jointly offered by Prof. Sandeep Juneja and Prof. Tushar Jaruhar. It introduces foundational models and computational techniques used in modern financial markets, with particular emphasis on implementation and applications to Indian markets.

Course Content

  • Basic interest rates, NPV, and internal rate of return
  • Fixed-income markets and term structure of interest rates
  • Portfolio theory and convex optimization review
  • Markowitz model, market equilibrium, and CAPM
  • Discrete- and continuous-time models for asset prices
  • Brownian motion and geometric Brownian motion. Introduction to Itô calculus.
  • Discrete options pricing and the Black–Scholes formula
  • Monte Carlo simulation and numerical PDE methods

Learning Outcomes

  • Understand core models used in quantitative finance
  • Apply portfolio theory and asset pricing models
  • Develop intuition for stochastic processes in finance
  • Implement computational methods for pricing and risk analysis
  • Analyze real-world financial data, with emphasis on Indian markets

Requirements & Reading List

  • Luenberger, D. (2009). Investment Science. Oxford University Press.
  • Shreve, S. (2005). Stochastic Calculus for Finance I. Springer.
  • Hull, J. C. & Basu, S. (2016). Options, Futures, and Other Derivatives. Pearson India.
  • Glasserman, P. (2004). Monte Carlo Methods in Financial Engineering. Springer.
  • Embrechts, P., Frey, R., & McNeil, A. (2011). Quantitative Risk Management.

Attendance Policy

  • 3 excused absences permitted for all students
  • Additional 3 excused absences permitted for sportspersons
  • Beyond this, a penalty of 1% per unexplained missed class will apply

Stochastic Calculus & Mathematical Finance

This is a course for advanced undergraduate and graduate students with an aptitude and interest in quantitative methods. The students will be exposed to no-arbitrage-based deep and beautiful ideas underlying mathematical finance. For this they will get an adequate exposure to stochastic calculus. Stochastic calculus is also relevant for the increasingly mainstream diffusion-based generative AI.

Course Period: Monsoon 2025.

Schedule: Tuesday & Thursday, 10:10 – 11:40 AM

Mode: Hybrid (In-person + Online)

Duration: 40 hours of rigorous lectures + student-led projects

Course Content

  • Review of Measure-Theoretic Probability
  • Martingales & Brownian Motion
  • Stochastic Calculus & Stochastic Integration
  • Itô's Formula & Girsanov's Theorem
  • Stochastic Differential Equations & PDE Connections
  • Discrete & Continuous-Time Pricing Theory
  • Stochastic Volatility Models & Interest Rate Models
  • PDEs in Finance

Eligibility

  • Advanced undergraduates & master's-level students
  • Strong background in Probability, Linear Algebra, and Analysis
  • Aptitude & interest in quantitative methods

Lectures

Lecture Notes

Prof. Sandeep Juneja

Prof. Sandeep Juneja

  • Professor of Computer Science at Ashoka University. Director, Safexpress Centre for Data, Learning and Decision Sciences
  • Former Professor at TIFR and IIT Delhi. Former Head of Quantitative Ops (Bank of America, India)
  • Taught at JP Morgan, Bank of America, Morgan Stanley, Nomura. Consulted with Research Wing of Reserve Bank of India
  • Research in Applied Probability, Financial Mathematics, Learning Theory

Aman Foujdar

Aman Foujdar

  • Research Assistant under Prof. Juneja at SCDLDS
  • Interested in Machine Learning, Deep RL, GenAI, Financial Markets
  • Mathematics & Computer Science at Ashoka University. President of the Ashoka QuantFin Club (AQFC).

exSPLOre

Explorations in Statistics, Probability, Learning, and Optimization (exSPLOre) is our flagship event featuring lectures from leading experts in the area. This page presents a curated selection of exSPLOre guest lectures focused on quantitative finance and optimization. Additional lectures are available on the our YouTube.

Coming soon...