3 papers in the archive (2026), average empirical rigor 7.7/10, average math complexity 6.5/10. Quadrant mix: Holy Grail ×3.
Works mostly in Volatility Modeling & Forecasting, Market Microstructure, High-Frequency Trading & Optimal Execution, Fixed Income & Interest Rates.
Frequent co-authors: Fabrizio Cipollini (1), Giulia Cruciani (1), Giampiero M. Gallo (1), Alessandra Insana (1), Fabio Spagnolo (1), Demetrio Lacava (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%).
VOLARE (VOLatility Archive for Realized Estimates - https://volare.unime.it) is an open research infrastructure providing standardized realized volatility and covariance measures constructed from ultra-high-frequency financial data. The platform processes tick-level observations across equities, exc
Covariance models describe the dynamics of conditional covariance matrices as functions of past variances and covariances and are widely used to model the joint evolution of financial asset returns. Their specification faces two major challenges: the curse of dimensionality, whereby the number of pa
This paper investigates the impact of Trade Policy Uncertainty (TPU) on stock-bond correlation dynamics in the United States. Using daily data on major U.S. stock indices and the 10-year Treasury bond from 2015 to 2025, we estimate correlation within a two-step GARCH-based framework, relying on mult