5 papers in the archive (2022–2025), average empirical rigor 3.8/10, average math complexity 8.2/10. Quadrant mix: Holy Grail ×2, Lab Rats ×3.
Works mostly in Options & Derivatives Pricing, Risk Management & Tail Risk, Stochastic Control & Optimal Stopping, Insurance & Actuarial Risk.
Frequent co-authors: Paweł Stȩpniak (3), Paweł Stępniak (1), Krzysztof Burnecki (1), Marek Teuerle (1), Aleksandra Wilkowska (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 this paper, we adopt the least squares Monte Carlo (LSMC) method to price time-capped American options. The aforementioned cap can be an independent random variable or dependent on asset price at random time. We allow various time caps. In particular, we give an algorithm for pricing the American
In this paper, we generalise the results presented in the literature for the ruin probability for the insurer–reinsurer model under a pro-rata reinsurance contract. We consider claim amounts that are described by a phase-type distribution that includes exponential, mixture of exponential, Erlang, a
We derive the explicit price of the perpetual American put option cancelled at the last passage time of the underlying above some fixed level. We assume the asset process is governed by a geometric spectrally negative Lévy process. We show that the optimal exercise time is the first epoch when asset
This paper presents a derivation of the explicit price for the perpetual American put option time-capped by the first drawdown epoch beyond a predefined level. We consider the market in which an asset price is described by geometric Lévy process with downward exponential jumps. We show that the opti
This paper presents a derivation of the explicit price for the perpetual American put option in the Black-Scholes model, time-capped by the first drawdown epoch beyond a predefined level. We demonstrate that the optimal exercise strategy involves executing the option when the asset price first falls