4 papers in the archive (2022–2025), average empirical rigor 5/10, average math complexity 6.9/10. Quadrant mix: Holy Grail ×3, Lab Rats ×1.
Works mostly in Crypto Markets & DeFi, Market Microstructure, Portfolio Optimization, Stochastic Control & Optimal Stopping.
Frequent co-authors: Philippe Bergault (4), Louis Bertucci (1), David Bouba (1), Bastien Baldacci (1), Alexander Barzykin (1), Malo Lemmel (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
In traditional financial markets, yield curves are widely available for countries (and, by extension, currencies), financial institutions, and large corporates. These curves are used to calibrate stochastic interest rate models, discount future cash flows, and price financial products. Yield curves,
This paper introduces a novel methodology for the pricing and management of share buyback contracts, overcoming the limitations of traditional optimal control methods, which frequently encounter difficulties with high-dimensional state spaces and the intricacies of selecting appropriate risk penalty
With the emergence of decentralized finance, new trading mechanisms called Automated Market Makers have appeared. The most popular Automated Market Makers are Constant Function Market Makers. They have been studied both theoretically and empirically. In particular, the concept of impermanent loss ha
Over the past decade, many dealers have implemented algorithmic models to automatically respond to RFQs and manage flows originating from their electronic platforms. In parallel, building on the foundational work of Ho and Stoll, and later Avellaneda and Stoikov, the academic literature on market ma