3 papers in the archive (2023–2025), average empirical rigor 5.8/10, average math complexity 6.8/10. Quadrant mix: Holy Grail ×2, Lab Rats ×1.
Works mostly in Options & Derivatives Pricing, Crypto Markets & DeFi, Volatility Modeling & Forecasting, Risk Management & Tail Risk.
Frequent co-authors: Francis Liu (1), Artur Sepp (1), Michael Kalkbrener (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 paper presents an option pricing model that incorporates clustered jumps using a bivariate Hawkes process. The process captures both self- and cross-excitation of positive and negative jumps, enabling the model to generate return dynamics with asymmetric, time-varying skewness and to produce po
Stress testing refers to the application of adverse financial or macroeconomic scenarios to a portfolio. For this purpose, financial or macroeconomic risk factors are linked with asset returns, typically via a factor model. We expand the range of risk factors by adapting dimension-reduction techniqu
We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time-homogeneous Markov chain. While the rating process itself possesses the Markov property o