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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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</article> </div>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. link.
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 link.
portfolio
Short description of portfolio item number 1
Short description of portfolio item number 2
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 link.
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.
</article> </div>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.
</article> </div>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.
</article> </div>workingpapers
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