3 papers in the archive (2023–2026), average empirical rigor 3/10, average math complexity 8.5/10. Quadrant mix: Lab Rats ×3.
Works mostly in Portfolio Optimization, Insurance & Actuarial Risk, Risk Management & Tail Risk.
Frequent co-authors: Sebastian Jaimungal (2), Silvana M. Pesenti (2), Mogens Steffensen (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 consider the problem of an agent who faces losses in continuous time over a finite time horizon and may choose to share some of these losses with a counterparty. The agent is uncertain about the true loss distribution and has multiple models for the losses. Their goal is to optimize a mean-varian
We study an investor’s optimal portfolio choice problem when they account for the impact of a possible future green transition, whose timing is uncertain. We model the green transition as a discontinuity in the stock price processes, driven by a single jump process with constant intensity, in which
We study a reinsurer who faces multiple sources of model uncertainty. The reinsurer offers contracts to $n$ insurers whose claims follow compound Poisson processes representing both idiosyncratic and systemic sources of loss. As the reinsurer is uncertain about the insurers’ claim severity distribut