4 papers in the archive (2022–2025), average empirical rigor 1.8/10, average math complexity 8.8/10. Quadrant mix: Lab Rats ×4.
Works mostly in Risk Management & Tail Risk, Stochastic Control & Optimal Stopping, Options & Derivatives Pricing, Insurance & Actuarial Risk.
Frequent co-authors: Francesca Biagini (3), Andrea Mazzon (2), Thilo Meyer-Brandis (1), Alessandro Gnoatto (1), Moritz Ritter (1), Thorsten Schmidt (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 most cases, insurance contracts are linked to the financial markets, such as through interest rates or equity-linked insurance products. To motivate an evaluation rule in these hybrid markets, Artzner et al. (2022) introduced the notion of insurance-finance arbitrage. In this paper we extend thei
We consider the pricing and hedging of counterparty credit risk and funding when there is no possibility to hedge the jump to default of either the bank or the counterparty. This represents the situation which is most often encountered in practice, due to the absence of quoted corporate bonds or CDS
In this paper we introduce a definition of a multi-dimensional fractional Brownian motion of Hurst index $H \in (0, 1)$ under volatility uncertainty (in short G-fBm). We study the properties of such a process and provide first results about stochastic calculus with respect to a fractional G-Brownian
This is a supplement to the paper “Liquidity based modeling of asset price bubbles via random matching”. The supplement is organized as follows. First, we prove Theorem 3.13 in [1] which provides the existence of the dynamical system D introduced in Definition 3.6 in [1]. Second, we show some proper