4 papers in the archive (2025–2026), average empirical rigor 4.5/10, average math complexity 8.1/10. Quadrant mix: Holy Grail ×2, Lab Rats ×2.
Works mostly in Crypto Markets & DeFi, Risk Management & Tail Risk, Stochastic Control & Optimal Stopping, Portfolio Optimization.
Frequent co-authors: Marcel Nutz (2), Natascha Hey (1), Ciamac C. Moallemi (1), Ting-Kam Leonard Wong (1), Agostino Capponi (1), Ananya Parashar (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%).
Passive liquidity providers (LPs) in automated market makers (AMMs) face losses due to adverse selection (LVR), which static trading fees often fail to offset in practice. We study the key determinants of LP profitability in a dynamic reduced-form model where an AMM operates in parallel with a centr
We study optimal portfolio choice for a household managing two goals at once. A random-deadline precautionary goal, such as a medical emergency, must be paid in full whenever it arrives and is affordable; a fixed-deadline accumulation goal, such as a target retirement lifestyle, may be declined at i
Auto-deleveraging (ADL) mechanisms are a critical yet understudied component of risk management on cryptocurrency futures exchanges. When available margin and other loss-absorbing resources are insufficient to cover losses following large price moves, exchanges reduce positions and socialize losses
We study the excess growth rate – a fundamental logarithmic functional arising in portfolio theory – from the perspective of information theory. We show that the excess growth rate can be connected to the Rényi and cross entropies, the Helmholtz free energy, L. Campbell’s measure of average code len