Methodology & Validation

How Market Predictions Become Verified Intelligence

Tahlil Plus turns raw analyst content into structured prediction records, tracks market outcomes, validates results and builds intelligence scores across analysts, symbols and markets.

Source-linked predictionsAI-normalized extractionOutcome validationReliability scoring
Intelligence Method
Explainable pipeline
Verified
Input
Raw Analysis
Output
Prediction Data
Validation
Outcome-based
Scoring
Multi-layer
Methodology Confidence
Extraction Structure92.00
Validation Logic88.00
Explainability90.00
Step 1
Extract
AI converts raw content into structured predictions
Step 2
Track
Prices are monitored after publication
Step 3
Validate
Signals are resolved by outcome behavior
Step 4
Score
Analysts and symbols receive intelligence metrics
Prediction Pipeline

From public analysis to structured intelligence

The system is designed to make market predictions measurable. Each stage reduces ambiguity and adds structure, validation and scoring context.

01

Collect

Market analysis content is monitored from public analyst sources.

The system tracks analyst posts and videos, stores source metadata and prepares content for AI extraction.

02

Extract

AI converts raw analysis into structured prediction records.

Symbols, market, direction, target price, invalidation price, timeframe and reasoning context are extracted and normalized.

03

Normalize

Predictions are converted into comparable intelligence objects.

Different analyst formats are standardized into one structure so predictions can be compared across crypto, stocks and forex.

04

Track

Prices are monitored after publication.

The system checks market movement after the signal is published and measures return, runup, drawdown and distance to target or invalidation.

05

Validate

Predictions are resolved into measurable outcomes.

Signals move through validation states such as checking, pending, correct, fail or awaiting validation depending on price behavior.

06

Score

Analysts, symbols and markets receive intelligence scores.

Reliability, success rate, consistency, risk/reward, quality and live performance are combined into intelligence layers.

Scoring Layers

Every score has a specific role

Tahlil Plus does not rely on one generic score. Different intelligence layers measure different questions: signal quality, analyst reliability and symbol-level consensus.

Score Layer

Signal Quality

Measures whether the prediction is understandable, actionable, price-aware and useful enough to contribute to intelligence metrics.

Principal
Comprehensible
Accurate
Actionable
Overall Quality
Score Layer

Analyst Reliability

Ranks analysts by verified prediction history, success rate, consistency, average return, risk behavior and market expertise.

Reliability
Success Rate
Consistency
Risk Adjusted
Time Efficiency
Score Layer

Symbol Intelligence

Aggregates active predictions, target consensus, directional consensus, analyst coverage and historical symbol-level success.

Prediction Direction
Target Consensus
Forward Consensus
Coverage
Opportunity
Validation Logic

Predictions are tracked after publication

A prediction is not trusted simply because it was published. The system monitors what happens after publication: whether price moves toward the target, hits invalidation, remains active or becomes eligible for scoring later.

Return
Performance after publish
Runup
Best favorable movement
Drawdown
Worst adverse movement
Time to Result
Resolution duration
Validation States

Forward Signal

Forward Signal

A prediction that is still active and can be tracked against future market movement.

Checking

Checking

A signal that has been extracted and is waiting for enough price movement or validation time.

Correct

Correct

A prediction that reached its target condition before invalidation.

Fail

Fail

A prediction that hit invalidation or failed according to the validation rules.

Consensus Intelligence

Individual predictions become market-level intelligence

When multiple analysts publish active predictions on the same symbol, the system builds forward consensus and target consensus layers.

Forward Consensus

Directional market expectation

Active signals are grouped by direction and weighted by analyst credibility, signal quality and market context. This creates a symbol-level view of bullish, bearish and range pressure.

64%
Bullish
28%
Bearish
8%
Range
Target Consensus

Weighted target expectation

Targets are aggregated into a weighted consensus target with confidence level, target dispersion and risk/reward context. This helps users understand not just direction, but expected destination and agreement strength.

Analyst Consensus Target
Weighted target price
Target Agreement Spread
How concentrated targets are
Consensus Risk / Reward
Reward potential vs invalidation risk
Important Context

Intelligence is not financial advice.

Tahlil Plus measures and structures public market predictions. It does not guarantee outcomes, recommend trades or replace independent research. The platform is designed to improve transparency around analyst predictions and market consensus.

No guarantee
Markets remain uncertain
Source-based
Built from public analysis
Outcome-aware
Predictions are validated over time
Decision support
Data layer, not trade instruction
Explore The System

See verified prediction intelligence in action.

Browse live predictions, symbol consensus, analyst profiles and ranking layers built from the methodology above.