Quantitative modeller in ALM & Treasury at BNL (BNP Paribas Group) and PhD candidate in Quantitative Finance at Sapienza University of Rome. I work where econometrics meets balance-sheet risk: interest-rate and behavioural models for banks, and Bayesian methods for yield curves, climate and energy risk.
- Bayesian econometrics — regime-switching and latent-state models, identification
- Term structure modelling — Dynamic Nelson–Siegel with time-varying transition probabilities
- Climate & energy finance — transition risk, power–gas markets, stress testing
- Generative scenarios & decision making — diffusion models, Bayesian optimisation, Gaussian processes
Quantitative models for ALM & Treasury: prepayment (CPR), non-maturity deposits (NMD) and client-rate models. (Industry work is proprietary and not published here.)
| Project | What it is |
|---|---|
| Keystone | Empirical asset-pricing research framework with formal overfitting control (CPCV, Deflated Sharpe Ratio, PBO). ~20 pre-registered experiments on a survivorship-free, point-in-time S&P 500 universe, with a public kill-log. 615 tests, CI. |
| Climate-Risk-Project | Credit spreads, yield curve and climate transition risk under SSP scenarios — long-horizon projections of the risk-free and credit curves. |
- Weak Identification and Attribution in Covariate-Driven Latent-State Models
- Weather Is Not the Stress Test — conditional diffusion models for power–gas stress testing (spark spreads, 2022 energy crisis)
- Bayesian Optimization of Risk-Mitigation Policies under Diffusion-Generated Energy Crisis Scenarios
Python · R · pandas · numpy · scipy · statsmodels · scikit-learn · PyTorch · cvxpy · pytest · uv · Git
- PhD candidate, Quantitative Finance — Sapienza University of Rome
- Executive Master, Quantitative Methods for Climate Risk — École Polytechnique
- Previously: quantitative consulting (Iason) · credit risk (BNL)
LinkedIn · 📍 Rome, Italy · feel free to reach out about research collaborations or quant roles.