3 papers in the archive (2022–2025), average empirical rigor 5.3/10, average math complexity 6.2/10. Quadrant mix: Holy Grail ×1, Lab Rats ×1, Street Traders ×1.
Works mostly in Market Microstructure, Market Simulation & Agent-Based Models, Volatility Modeling & Forecasting, NLP & LLMs in Finance.
Frequent co-authors: Mathieu Rosenbaum (2), Perukrishnen Vytelingum (1), Rory Baggott (1), Namid Stillman (1), Dingqiu Zhu (1), Tao Chen (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%).
Given the promising results on joint modeling of SPX/VIX smiles of the recently introduced quadratic rough Heston model, we consider a multi-asset market making problem on SPX and its derivatives, e.g. VIX futures, SPX and VIX options. The market maker tries to maximize its profit from spread captur
In this paper, we describe a novel agent-based approach for modelling the transaction cost of buying or selling an asset in financial markets, e.g., to liquidate a large position as a result of a margin call to meet financial obligations. The simple act of buying or selling in the market causes a pr
News can convey bearish or bullish views on financial assets. Institutional investors need to evaluate automatically the implied news sentiment based on textual data. Given the huge amount of news articles published each day, most of which are neutral, we present a systematic news screening method t