Our system is built to surface probabilities, not promises. Here's how each piece works.
Every name in the large-cap universe is scored by nine academically-documented factor models — value, momentum, quality, profitability, investment, size, volatility, and more. Each model is evaluated on the stock's own earnings clock, the period between its earnings announcements, so that timing matters.
The composite score weights each model by its walk-forward-validated predictive power. A model that only worked in backtests gets a smaller vote than one that has continued to work on data it never saw during development.
Macro context is anchored to FRED data releases and prediction-market odds — not sentiment or headlines. When the model references GDP growth, inflation expectations, or rate probabilities, those numbers come from the Federal Reserve's own datasets or from markets where real money is on the line.
Every sector-level stance passes through a challenge layer that looks for stale evidence and forces disputed claims to earn their place or get struck from the thesis.
The candidates are chosen by the quantitative scores, then argued by a committee in which each step is seated by the model that leads that kind of financial work: a bear reading the company's filings and headlines for red flags, a bull answering it, and a judge from a different lab deciding which names stay. Disagreement is never a reason to keep a name.
A trader sizes the book, three risk reviewers may shrink or veto positions but not reopen the argument, and a final manager — never the model that wrote the book — confirms it. A hard validation gate then checks every ticker and every weight, or the book does not ship.
Once you build a position, the system monitors for drift, drawdown, concentration, and thesis-break events. When something triggers, you receive an alert with the reasoning.
You approve or reject every rebalance. Nothing trades on its own. The system proposes; you decide.
When we cite composite-decile returns (e.g., "top decile averaged 15.6% annually"), those figures come from an out-of-sample validation period — data the models did not see during development. Still:
Treat these numbers as evidence that the scoring system captured something real in the validation window — not as a forecast of your personal returns.
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Sanctuary Research provides quantitative investment research and educational content — not personalized investment advice. Markets involve risk; do your own due diligence.