3 papers in the archive (2024), average empirical rigor 5.2/10, average math complexity 7.8/10. Quadrant mix: Holy Grail ×2, Lab Rats ×1.
Works mostly in Fixed Income & Interest Rates, Risk Management & Tail Risk, Options & Derivatives Pricing.
Frequent co-authors: Ahmed Kebaier (2), Djibril Sarr (2), Martin Friesen (1), Jonas Kremer (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%).
This research presents a comprehensive framework for transitioning financial diffusion models from the risk-neutral (RN) measure to the real-world (RW) measure, leveraging results from probability theory, specifically Girsanov’s theorem. The RN measure, fundamental in derivative pricing, is contrast
This paper introduces a novel stochastic model for credit spreads. The stochastic approach leverages the diffusion of default intensities via a CIR++ model and is formulated within a risk-neutral probability space. Our research primarily addresses two gaps in the literature. The first is the lack of
We study the Volterra Volterra Cox-Ingersoll-Ross process on $\mathbb{R}_+$ and its stationary version. Based on a fine asymptotic analysis of the corresponding Volterra Riccati equation combined with the affine transformation formula, we first show that the finite-dimensional distributions of this