3 papers in the archive (2025), average empirical rigor 3.8/10, average math complexity 8.5/10. Quadrant mix: Holy Grail ×1, Lab Rats ×2.
Works mostly in Statistical Arbitrage & Pairs Trading, Portfolio Optimization, Market Microstructure, Stochastic Control & Optimal Stopping.
Frequent co-authors: Balint Binkert (1), Paul Mangers Bastian (1), Josef Teichmann (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%).
We develop a framework for stochastic portfolio theory (SPT), which incorporates modern nonlinear price impact and impact decay models. Our main result is the derivation of the celebrated master formula for additive functional generation of trading strategies in a general high-dimensional market mod
Drifts of asset returns are notoriously difficult to model accurately and, yet, trading strategies obtained from portfolio optimization are very sensitive to them. To mitigate this well-known phenomenon we study robust growth-optimization in a high-dimensional incomplete market under drift uncertain
We study a consumption-investment problem in a multi-asset market where the returns follow a generic rank-based model. Our main result derives an HJB equation with Neumann boundary conditions for the value function and proves a corresponding verification theorem. The control problem is nonstandard d