INTEGRITY ENGINE

The Reliability Score for Every Market

A real-time 0–100 market integrity score that reveals the true quality, stability, and trustworthiness behind every price.

Market Integrity Analysis

Target: FED_RATE_DEC_2024

94/100
HIGHLY RELIABLE
Liquidity Depth
98
Volatility Stability
92
Historical Pattern
95
Manipulation Risk
99
Rule Clarity
88

What Is the Integrity Engine?

Integrity Engine is WagerKit's real-time quantitative model that evaluates how reliable and manipulation-free a prediction market is. It converts billions of data points into a single integrity score.

Is this market trustworthy?

Are prices stable?

Is liquidity strong?

Is someone manipulating?

Can analysts rely on this?

Why It Matters

Prediction markets look simple — but underneath they are highly volatile, prone to manipulation, and sensitive to bad news.

  • Vulnerable to low liquidity
  • Influenced by whales
  • Mispriced across platforms
  • Sensitive to flash crashes
Integrity Engine solves this by rating markets like a credit score.
0-100
Standardized Score

Core Components of the Integrity Score

1. Liquidity Depth Analysis

Understands order book strength, spread tightness, volume density, and slippage resistance. Identifies fragile markets.

2. Volatility Stability Layer

Tracks price jumps, flash micro-movements, whiplash volatility, and abnormal reversals. Detects short-term shocks.

3. Historical Pattern Model

Compares live movements with long-term patterns to flag unusual correlations and inconsistent price structures.

4. Manipulation Probability

Flags behaviors like whale spoofing, volume attacks, pump-and-reverse, and spread widening tactics.

5. Market Clarity Score

Rates clarity of market rules, resolution conditions, and data sources. Markets with vague rules score lower.

Understanding the Score

80–100
Highly Reliable
60–79
Stable
40–59
Caution
20–39
High Risk
0–19
Unreliable

Who Uses Integrity Engine?

Algorithms filtering low-integrity markets
Platforms displaying credibility badges
Compliance teams getting risk insights
Traders avoiding fake signals
Reporters needing trust metrics