TMS Score (Event-Significance Score)

TMS is the event-significance score used by TradeAI News to quantify how significant a detected market event is, on a 0–100 scale. Every event the platform detects — a news catalyst, an unusual-volume reading — is scored as it is processed. The TMS is the output of the multi-factor scoring engine, combining news catalyst classification, unusual-volume detection and options-market context into a single number. It measures significance and magnitude, never direction.

A higher TMS means the event more closely resembles those that have historically preceded significant near-term price movement — in either direction. Lower scores mark events that are logged but not treated as high priority. The score measures significance, never direction.

TMS Tiers and Alert Actions

WATCH (55–67): Events in this range are logged and visible in the dashboard but do not trigger push alerts. They represent interesting but lower-confidence situations worth monitoring — a moderate catalyst with limited confirming data.

SEND PREMIUM (68–81): Events in this range trigger alerts to Pro and Elite plan subscribers via Telegram. They represent elevated evidence that a meaningful move is likely — typically a strong catalyst with one or two confirming readings (unusual volume or options context) but not full convergence.

SEND NOW (82–100): The highest tier. Events at 82+ trigger immediate alerts to all paying subscribers. These represent maximum convergence: a strong catalyst with confirming unusual volume and elevated options-market readings. TradeAI News publishes no accuracy or win-rate figure for any tier: the score encodes how much independent evidence converged, not a validated probability of a move in any direction.

What Factors Drive the TMS Score

The TMS score is a weighted composite of: catalyst type and estimated significance (the largest weighting), unusual volume relative to baseline, the ticker's historical sensitivity to this catalyst type, current short interest and float data, and sector momentum context. The exact weighting is proprietary and subject to ongoing model refinement.

TMS vs Raw Layer Scores

Individual data streams (news alone, options context alone, volume alone) each produce their own sub-scores. The TMS integrates these sub-scores rather than averaging them — meaning that convergence across multiple data types produces a disproportionately high TMS score, reflecting the statistical edge that multi-factor alignment creates over any single data stream.