4 papers in the archive (2025–2026), average empirical rigor 7.2/10, average math complexity 6.9/10. Quadrant mix: Holy Grail ×3, Lab Rats ×1.
Works mostly in Fixed Income & Interest Rates, Options & Derivatives Pricing, Risk Management & Tail Risk, Volatility Modeling & Forecasting.
Frequent co-authors: Marco Scaringi (2), Stefano Scoleri (1), Sergei Kucherenko (1), Giorgia Rensi (1), Pietro Rossi (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%).
The SABR model is a cornerstone of interest rate volatility modeling, but its practical application relies heavily on the analytical approximation by Hagan et al., whose accuracy deteriorates for high volatility, long maturities, and out-of-the-money options, admitting arbitrage. While machine learn
Risk allocation, the decomposition of a portfolio-wide risk measure into component contributions, is a fundamental problem in financial risk management due to the non-additive nature of risk measures, the layered organizational structures of financial institutions, and the range of possible allocati
Quasi Monte Carlo (QMC) and Global Sensitivity Analysis (GSA) techniques are applied for pricing and hedging representative financial instruments of increasing complexity. We compare standard Monte Carlo (MC) vs QMC results using Sobol’ low discrepancy sequences, different sampling strategies, and v
An important step in the Financial Benchmarks Reform was taken on 13th September 2018, when the ECB Working Group on Euro Risk-Free Rates recommended the Euro Short-Term Rate ESTR as the new benchmark rate for the euro area, to replace the Euro OverNight Index Average (EONIA) which will be discontin