Prediction Market Alpha Engines

Executive Overview

These strategies are designed for prediction markets where prices represent implied probabilities. The framework combines:

• Price Action
• Volume Analysis
• Open Interest
• Probability Surface Modeling
• Statistical Arbitrage

to generate systematic trading signals.

1. Momentum Indicator

A trend-following indicator that identifies contracts experiencing strong directional price movement alongside increasing volume and participation. It aims to capture institutional and retail capital flows by detecting sustained momentum and generating signals in the direction of the prevailing market trend.

Objective

Capture institutional and retail capital flows through price breakouts and volume expansion.

Signal Logic

Momentum Score =
Price Velocity × Volume Shock × Liquidity Factor

Example

Signal: BUY YES

2. Volume Shock Indicator

An order-flow indicator that detects abnormal trading activity by measuring 24-hour volume relative to open interest. When new trading volume significantly exceeds existing positions, it signals aggressive capital inflows and potential breakout opportunities before they become widely recognized.

Objective

Identify aggressive institutional accumulation before broad market participation.

Formula

Volume Shock Ratio =
24h Volume / Open Interest

Example

Result:

90,000 / 15,000 = 6.0

A value significantly above historical norms indicates abnormal capital inflow.

3. Peer Residual Indicator

A statistical arbitrage indicator that compares a contract’s price against a group of highly correlated peers. It identifies contracts that have deviated significantly from the peer group’s average behavior and generates mean-reversion signals when pricing becomes statistically abnormal.

Objective

Detect contracts deviating materially from highly correlated peers.

Example

Tesla becomes a potential mean-reversion candidate.

Signal: BUY NO

4. Curve Residual Indicator

A probability-surface indicator that evaluates contracts within ordered threshold markets against the market-implied distribution curve. It identifies strikes that trade materially above or below their calculated fair value, creating opportunities to profit from eventual normalization of the curve.

Objective

Find contracts deviating from the market-implied probability curve.

Example

Expected distributions should remain smooth.

When a strike deviates significantly from the implied curve, a residual opportunity is created.

Signal: BUY NO on the inflated strike.

5. Convexity Residual Indicator

A micro-structure indicator that detects localized distortions in the probability curve by analyzing the relationship between adjacent strikes. It identifies contracts whose pricing creates abnormal curvature relative to neighboring contracts and targets mean reversion when these structural anomalies correct.

Objective

Identify local distortions between neighboring strikes.

Example

The >5% strike is inflated relative to adjacent strikes.

Signal: BUY NO

6. Overround Residual Indicator

A relative value indicator that measures the difference between a contract’s market-implied probability and its vig-adjusted fair probability. Higher residual values indicate greater overpricing, making the contract a stronger candidate for contrarian or fade positions.

Objective

Measure pricing inefficiency after removing market vig.

Example

Total = 107

Fair YES Probability
= 65 / 107
= 60.7%

ORI = Market Price − Fair Probability

Higher ORI values indicate stronger fade opportunities.

7. Monotonicity Violation Indicator

A structural arbitrage indicator that identifies mathematical inconsistencies in cumulative threshold markets. It detects situations where higher-threshold contracts trade at probabilities greater than lower-threshold contracts, violating fundamental probability rules and creating low-risk arbitrage opportunities.

Objective

Exploit structural probability violations.

Example

This is mathematically impossible because:

P(>4%) <= P(>3%)

Signal: BUY NO on >4%

Composite Alpha Framework

Final Alpha Score = Weighted Indicator Score

Example

Final Alpha Score = 87/100

Trade Lifecycle

Institutional Edge

The framework does not attempt to predict event outcomes directly.

Instead, it extracts alpha from:

• Capital Flow Detection
• Statistical Mean Reversion
• Structural Arbitrage
• Probability Curve Inefficiencies
• Institutional Order Flow

This creates repeatable opportunities regardless of the underlying event outcome.