MSc Finance (110/110 cum laude), Università Cattolica del Sacro Cuore, Milan | Derivatives, Volatility & Python
I study how trading strategies behave once real-world frictions are priced in: execution costs, fill assumptions, margin and data quality. Most of my projects start from a published or personal strategy and end with one question: which assumption is actually carrying the result?
Interests: options and implied volatility, futures, execution and market microstructure, robust backtesting.
Replication of Zarattini & Aziz (2023), followed by an execution stress test. The paper's $138,639 backtest profit falls to $4,860 with 2¢ per share of slippage; break-even is about 2.2¢, against a spread of roughly 1¢. An NQ futures confirmation filter carries real information (t = 2.05, against 1.27 for a placebo), but 76% of the filtered profit comes from 2022 alone.
Replication of Zarattini, Aziz & Barbon (2024) on SPY, cross-validated on ES futures from a second data vendor (return correlation 0.97). Sharpe 1.11 with near-zero market beta. Optimisation does not improve it: with protocols frozen before any result and a Deflated Sharpe Ratio correction, the best of 27 variants is the paper's own setup, and quarterly walk-forward reselection cuts Sharpe from 0.92 to 0.57.
Ten years of one-minute Nasdaq-100 futures data. Eleven simulation corrections net out to +1.1% of PnL, while a single entry-fill assumption moves it by 15.7%. The result is reported as a Sharpe band (1.02 to 1.11) rather than a single point.
A systematic short-volatility strategy on Deribit BTC options, delta-hedged with futures. The code is being revised and will be published here; available on request in the meantime.
Python (pandas, NumPy, SciPy, statsmodels), pytest and GitHub Actions, Jupyter. Market data through the Interactive Brokers, Alpaca and Deribit APIs.
- MSc in Finance, Università Cattolica del Sacro Cuore, Milan: 110/110 cum laude, GPA 30/30. Coursework in Derivatives, Advanced Derivatives, Econometrics and Quantitative Methods for Finance
- Exchange semester, Butler University, Indianapolis: GPA 4.0/4.0
- BSc in Business Administration, Ca' Foscari University of Venice: thesis on market inefficiencies using Python-based regression analysis