Stock / source before conclusion
The reason behind a stock decision,
starting with its sources.
Vectus distinguishes the sources and dates of market data received under a formal agreement and verified filings. It shows applicable calculations and risk conditions alongside their evidence. When conditions are not met, it gives the reason and defers the judgment.
Stock and fund decisions: invite-only testThe moving lines explain the decision flow. They are not live stock data or trading signals.
How it works
Make the reason for a decision inspectable.
The useful answer is more than a one-line result. Check which source and date were used, whether the observations were sufficient, and why a judgment was deferred.
- First check the supported stock, source, and date.
- Do not treat prices and filings from different effective dates as one fact.
- If observations or linkage are insufficient, do not force a conclusion.
What the customer sees
A supported judgment and a deferral are different outcomes.
For example, a newly verified filing may take effect after the price date. It cannot be presented as already reflected in that earlier price. Vectus separates the dates and evidence, leaving what needs another check visible.
These are illustrative states, not an actual stock screen or customer account.
Evidence is linked
Only items with checked sources, dates, and scope are presented as decision evidence.
Timing or data insufficient
Missing data or a date mismatch remains visible with the reason for another check.
Follow-up observations do not guarantee investment performance.
Recommendation history
Separate the original decision from what happened later.
Vectus recommendation history separates the original judgment from observations after 5, 20, and 60 business days. A checkpoint is not reported as a result before it arrives. Source and date are checked in supported screens.
Model scope / precise, not inflated
Different questions call for different calculations.
Calculations and evidence
Vectus first checks sources, dates, and observation conditions. It shows evidence when conditions are met and a reason to defer when they are not.
Market regime
For applicable targets with sufficient history, statistical models including HMM examine market regimes and signs of change. Targets and time windows remain distinct.
Where the trained GNN applies
The trained GNN informs ETF risk propagation in the ETF allocation cap of EMP construction. This is separate from predicting a stock-price rise.