3 papers in the archive (2024–2026), average empirical rigor 8/10, average math complexity 6.5/10. Quadrant mix: Holy Grail ×3.
Works mostly in Risk Management & Tail Risk.
Frequent co-authors: Anna Mancini (2), Massimiliano Fessina (1), Tiziano Squartini (1), Pablo Astudillo-Estévez (1), Stefan Thurner (1), Diego Garlaschelli (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%).
Recent crises like the COVID-19 pandemic and geopolitical tensions have exposed vulnerabilities and caused disruptions of supply chains, leading to product shortages, increased costs, and economic instability. This has prompted increasing efforts to assess systemic risk, namely the effects of firm d
Production networks constitute the backbone of every economic system. They are inherently fragile as several recent crises clearly highlighted. Estimating the system-wide consequences of local disruptions (systemic risk) requires detailed information on the supply chain networks (SCN) at the firm-le
Assessing the resilience of the economy requires accounting for its intrinsic multi-layer nature, by assessing for instance how disruptions at the firm level spread through the production network and propagate to the banking sector. Methods exist to measure the reverberation of shocks over the multi