Methodology (high level)

This page explains how Hyperscanner thinks about signals, outcomes, and historical matching—without formula dumps or promises of profit.

Signals & lifecycle

The technical scanner surfaces candidate setups from market data using rules you configure (timeframe, risk appetite, filters, etc.). When a signal is active, the app may track it until take-profit, stop-loss, expiry, or another terminal state. “Expired” means the observation window ended without a defined win/loss outcome in the way we label it in the archive.

Performance stats

The performance views aggregate completed and tracked instances: win rates, hit counts, and summaries over time. These numbers describe what the system recorded, not a guarantee of future performance. Slippage, fees, funding, and execution differ by exchange and user.

Sentiment scanner & history

The sentiment scanner compares current combinations of indicators (regime/signature) to past dates when similar conditions occurred. Charts show price paths around those historical points. Similarity is a model choice inside the product; it is exploratory, not a forecast.

Data sources

Widgets and prices aggregate third-party APIs and exchange data. Latency, outages, or definition changes at a provider can affect readings. Widget help (“i”) panels describe what each reading is meant to represent.

Details can change as the product evolves. For the exact behavior of a live metric, rely on in-app labels and timestamps. Nothing here is personalized investment advice.