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Posts

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conferences

Cartea, Á., Drissi, F., & Monga, M. Execution and statistical arbitrage with signals in multiple automated market makers.
2023. IEEE 43rd International Conference on Distributed Computing Systems.
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Waldon, H., Drissi, F., Limmer, Y., Berdica, U., Foerster, J. N., & Cartea, A. DARE: The Deep Adaptive Regulator for Control of Uncertain Continuous-Time Systems.
2024. ICML 2024 Workshop: Foundations of Reinforcement Learning and Control--Connections and Perspectives
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portfolio

Short description of portfolio item number 1

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publications

Bergault, P., Drissi, F., & Guéant, O. Multi-asset Optimal Execution and Statistical Arbitrage Strategies under Ornstein-Uhlenbeck Dynamics.
2022. SIAM Journal on Financial Mathematics.
link.

Drissi, F. Solvability of differential Riccati equations and applications to algorithmic trading with signals.
2022. Applied Mathematical Finance
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Cartea, Á., Drissi, F., & Monga, M. Predictable losses of liquidity provision in constant function markets and concentrated liquidity markets.
2023. Applied Mathematical Finance.
link, code.

Cartea, Á., Drissi, F., & Monga, M. Decentralised finance and automated market making: Predictable loss and optimal liquidity provision.
2024. SIAM Journal on Financial Mathematics.
link.

talks

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teaching

Computer C++ and Applications to Quantitative Finance

Graduate course, Université Paris 1 Panthéon‑Sorbonne, 2022

This course introduces students to object-oriented programming by exploring the concepts of program specification and design, algorithm development, coding, and testing, with applications to designing a financial pricing library with pricing algorithms for vanilla and path-dependent options.

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Market Microstructure and Algorithmic Trading

Graduate course, University of Oxford - Mathematical and Computational Finance MSc, 2024

This course covers different models of Algorithmic and High Frequency trading for optimal execution and optimal market making.

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Continuous-Time Finance

Graduate course, University of Oxford - Saïd Business School - MSc Financial Economics, 2025

This course introduces stochastic calculus and aims at understanding how it can be applied to the pricing and hedging of financial contracts, such as equity options and interest rate derivatives. This course equips students with the probabilistic techniques required to understand the most widely used financial models.

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workingpapers

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Published: link.