Structured market prediction extracted from social analysis, normalized by AI, enriched with validation metrics, analyst reliability, live position tracking and source-level evidence.
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Entry, target and invalidation logic
The original analyst prediction is converted into a structured intelligence object with price mentions, normalized direction, target distance, invalidation distance and risk/reward context.
AI quality scoring
Each signal is scored for clarity, accuracy, actionability and overall usefulness before it contributes to intelligence metrics.
Quality intelligence locked
Detailed AI quality scores are part of the premium prediction case file.
What happened after publication?
The platform tracks price movement after publication and records outcome, runup, drawdown and resolution metadata.
Who generated this prediction?
Source, summary and reference
This is exactly how I trade SMC full time. I start by defining my directional bias on the higher time frame. Higher highs, higher lows, and recent breaks of structure tell me I’m only looking for buys. From there, I draw my Fibonacci from the external low to the external high to define my OTE. When that OTE aligns with a fair value gap from displacement, that’s my area of interest. I wait for price to fully retest that area. No chasing. No guessing. Once price taps in, I drop to the lower time frame to confirm buyers have taken control. Then I set my entry at the next fair value gap, keep my stop below structure, and target the recent high for a clean 3R setup. This isn’t signals. It’s a repeatable process. If you want more breakdowns like this, follow along. #smc #priceaction #forextrading #daytrader #smartmoneyconcepts #tradingstrategy #forexed #fvg #ote #shorts
Scoring and consensus eligibility
These fields explain whether this prediction is already verified, whether it contributes to analyst scoring, and whether it is included in symbol target consensus.