About
Founder-led. Evidence-first.
A quantitative equity research project developing systematic strategies that combine human judgement with machine-scale research. Born in Milan. Now in real-money live trading.
A quantitative equity research project founded by , developing systematic strategies that combine human judgement with machine-scale research. Born in Milan. Now in real-money live trading.
Founder-led Explain it. Test it. Document it.
VetraSquare is founder-led. The founder set the research standard: an internal paper for every strategy model, stating the question, the evidence, the limitations and the next research decision.
VetraSquare was founded by and is founder-led. The founder’s standard is an internal paper for every strategy model, stating the question, the evidence, the limitations and the next research decision.
The name comes from Piazza Vetra, a square in Milan.
What we are, and what we are not
We are
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Systematic
Model positions follow documented, systematic rules.
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Market-neutral research
We study how models can limit dependence on market direction.
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Evidence-first
Every model must rest on a written research case.
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Portfolio-minded
Risk is assessed across the combined model portfolio.
We are not
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A bet on market direction
Model portfolios are built around the spread between long and short positions, not the direction of the market.
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A guarantee
Market neutrality and diversification are objectives. Losses can occur in rising and in falling markets.
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Ideas without evidence
An idea needs an economic explanation and evidence after costs before it merits further development.
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Set and forget
A model must continue to justify its assumptions.
One platform from research to live trading
VetraSquare’s proprietary platform connects a research hypothesis to a tested model and its live implementation:
Research
Designed for a documented hypothesis and data aligned to when it was available.
Validation
Designed for walk-forward evaluation after costs.
Model portfolio
Testing correlations, overlapping model positions and implementation assumptions.
Risk analysis
Analysing model exposure, concentration and liquidity assumptions.
Simulation
Estimating trading costs, financing and short-borrow constraints.
Our development path moves from research through backtesting and live paper trading to real-money live trading, our current stage. We use AuditZK for track-record verification and plan to build at least 12 months of real-money trading evidence before any readiness decision on an investor launch. That decision also depends on the evidence, operating arrangements and applicable requirements.
Our research approach
Next: our approach
Research objectives, portfolio constraints and the principles that guide strategy development.