Eduardo Abi Jaber.

Teaching

From foundations
to applications.

Courses in stochastic modelling, memory, quantitative finance and learning, for graduate students and practitioners.

Master’s course

Stochastic Modelling and Derivatives

M2 Probabilités et Finance · École Polytechnique & Sorbonne Université

Stochastic modelling for financial derivatives.

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Third-year course

Quantitative Finance: Models, Data & Learning

École Polytechnique · 3A

Quantitative finance at the interface of mathematical models, data and learning.

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Master’s course

Memory in Quantitative Finance: Volterra Processes and Path Signatures

M2 Probabilités et Finance · École Polytechnique & Sorbonne Université

A course connecting stochastic models with memory and path-signature methods. Created in 2023 and taught annually.

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Master’s course

Data Challenge

M2 Probabilités et Finance · École Polytechnique & Sorbonne Université

Learning from data through applied challenges.

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Previous teaching

Lectures
  • 2022–2025 · École Polytechnique: Deep Learning in Finance (MSc Data Science in Finance, École Polytechnique–HEC).
  • 2021–2022 · ENSAE: Numerical Methods in Financial Engineering (3A, 12h); Introduction to Mathematical Finance (2A, 18h).
  • 2019–2022 · Université Paris 1 Panthéon-Sorbonne: Market Risk Measures (M2, 18h); Calibration in Quantitative Finance (M2, 18h); Topics in Machine Learning (M2, 18h).
Tutorial classes
  • 2022 · École Polytechnique: Markov Chains and Martingales (MAP432, 20h).
  • 2019–2022 · Université Paris 1 Panthéon-Sorbonne: Mathematics of Insurance and Risks (M2, 16h); Mathematical Finance (M1, 24h); Integration and Probability (L3, 42h); Analysis (L3, 42h); Linear Algebra (L2, 30h).
  • 2016–2018 · Université Paris Dauphine: Jump Processes, Valuation and No Arbitrage (M2 MASEF).