Commit-Reveal Markets

#Definition

A commit-reveal market is a prediction market structure that uses sealed predictions to prevent herding behavior. Traders first commit to predictions cryptographically without revealing them, then reveal their forecasts after a deadline. This two-phase process ensures all predictions are made independently, eliminating the ability to copy or react to others' views.

The mechanism borrows from cryptographic commit-reveal schemes used in blockchain systems and auction design. By separating the commitment and revelation phases, these markets extract genuine independent beliefs from participants rather than consensus-following behavior that can plague open prediction markets.

Taxonomy Note: The primary goal of a commit-reveal market is to prove independent forecasts. By keeping predictions sealed until the reveal phase, it prevents herd behavior and ensures true independent signal aggregation.

As part of the foundational and aggregation mechanisms category in prediction market design, commit-reveal markets use sealed-bid predictions that are revealed later, specifically designed to prevent herding and ensure independent forecasts. This aggregation approach produces more accurate collective predictions by eliminating social influence during the forecasting phase.

#Why It Matters in Prediction Markets

Commit-reveal markets address fundamental problems with information cascades and social influence in forecasting.

Eliminating herding

In open markets, traders observe others' positions and prices, creating incentives to follow rather than think independently. Early predictions influence later ones, potentially amplifying errors. Commit-reveal markets break this chain; every prediction reflects only the trader's own analysis, not reactions to visible consensus.

True information aggregation

Prediction markets theoretically aggregate diverse information from many independent sources. But if traders copy each other, the market aggregates fewer truly independent signals. Commit-reveal ensures n traders provide n independent data points, maximizing the wisdom-of-crowds effect.

Reduced manipulation vectors

Open markets allow manipulation through visible position-taking that influences others. A whale buying Yes signals confidence, potentially triggering followers. In commit-reveal markets, no one sees positions until everyone has committed, eliminating this social manipulation channel.

Honest expression of uncertainty

When predictions are visible, traders may avoid expressing uncertainty or contrarian views due to reputational concerns. Sealed commitments allow honest probability estimates without social pressure, producing better-calibrated forecasts.

#How It Works

#Two-Phase Structure

Phase 1: COMMIT
├── Traders submit sealed predictions
├── Commitments are cryptographic hashes (not readable)
├── No one can see others' predictions
├── Deadline enforced; no changes after commit
└── Duration: Hours to days depending on market

Phase 2: REVEAL
├── Traders reveal actual predictions
├── Platform verifies reveals match commitments
├── All predictions become visible simultaneously
├── Invalid or missing reveals are penalized
└── Market resolves based on revealed predictions

#Cryptographic Commitment

The commit phase uses hash functions to seal predictions:

Commitment = Hash(Prediction + Secret + Trader_ID)

Example:
├── Prediction: "Yes at 73%"
├── Secret: "x7Kp2mNq" (random string)
├── Trader_ID: "trader_123"
└── Commitment: "0xa3f8d2e1..." (hash output)

The commitment reveals nothing about the prediction but uniquely identifies it. During reveal, the trader submits the original inputs; the platform verifies the hash matches.

#Reveal Verification

Verification Process:
1. Trader submits: (Prediction, Secret, Trader_ID)
2. Platform computes: Hash(Prediction + Secret + Trader_ID)
3. Platform compares computed hash to stored commitment
4. If match: Prediction accepted
5. If mismatch: Prediction rejected, penalties apply

This makes it cryptographically impossible to change predictions after seeing others' reveals.

// Example: Creating a cryptographic commitment (using ethers.js style)
const { ethers } = require("ethers");

function createCommitment(predictionValue, secretSalt) {
  // Hash the prediction combined with a secret salt
  // This produces a unique string that hides the value but locks it in
  const commitment = ethers.utils.solidityKeccak256(
    ["string", "string"], 
    [predictionValue, secretSalt]
  );
  return commitment;
}

// Usage
const myPrediction = "YES";
const mySecret = "correct-horse-battery-staple"; // Keep this safe!
const hashToSubmit = createCommitment(myPrediction, mySecret);

console.log("Submit this hash:", hashToSubmit);
// Later, you reveal "YES" and "correct-horse-battery-staple"
// The contract verifies the hash matches.

#Numerical Example

A commit-reveal market asks whether a merger will receive regulatory approval:

Commit Phase (Days 1-7):

During commit phase, no trader knows others' predictions. Each commits based solely on their own analysis.

Reveal Phase (Day 8):

All traders reveal simultaneously:

Alice reveals: Yes at 65% ✓ (hash matches)
Bob reveals: Yes at 45% ✓ (hash matches)
Carol reveals: No at 60% ✓ (hash matches)
David reveals: Yes at 70% ✓ (hash matches)
Eve: No reveal submitted ✗ (penalty applied)

Aggregation:

Valid predictions: 4
Yes predictions: 3 (Alice 65%, Bob 45%, David 70%)
No predictions: 1 (Carol 60%)

Aggregate forecast:
Average Yes probability = (65% + 45% + 70% + (100%-60%)) / 4 = 55%

Resolution: Merger approved → Yes was correct

Payouts: Based on accuracy scoring (Brier score, log score, or similar) applied to revealed predictions.

#Payout Structures

Commit-reveal markets commonly use proper scoring rules:

Brier Score Example:

Carol predicted No at 60% (meaning Yes at 40%). Outcome was Yes.

Brier Score = (0.40 - 1.00)² = 0.36 (higher is worse)

Alice predicted Yes at 65%. Outcome was Yes.

Brier Score = (0.65 - 1.00)² = 0.1225 (lower is better)

Alice receives larger payout share due to better calibration.

#Examples

#Example 1: Election Forecasting

A commit-reveal market aggregates election predictions:

• Commit phase opens 30 days before election
• Analysts, pollsters, and traders submit sealed probability estimates
• No one sees others' forecasts during analysis period
• Reveals occur 7 days before election; aggregate published
• Post-election, accurate forecasters receive bounty shares

The sealed structure prevents analysts from anchoring on early polls or each other's models.

#Example 2: Economic Indicator Prediction

A commit-reveal market forecasts monthly jobs numbers:

• Commit deadline: 48 hours before data release
• Economists submit point estimates and confidence intervals
• All predictions sealed until 1 hour before release
• Simultaneous reveal creates consensus forecast
• Accuracy scoring determines payout distribution

Independence ensures the aggregate reflects diverse economic models rather than groupthink.

#Example 3: Scientific Replication Prediction

A commit-reveal market asks whether a published study will replicate:

• Researchers commit predictions based on methodology review
• Sealed format prevents reputation signaling from influencing others
• Reveals after replication study design is locked
• Resolution upon replication results
• Identifies which researchers can accurately assess replication likelihood

#Example 4: Product Launch Success

A commit-reveal market predicts whether a product launch will meet targets:

• Industry analysts commit predictions based on private research
• Competitive intelligence prevents sharing during commit phase
• Reveals create pre-launch consensus
• Post-launch metrics determine resolution
• Analysts build track records based on independent accuracy

#Example 5: Geopolitical Events

A commit-reveal market forecasts diplomatic outcomes:

• Experts from different organizations commit independently
• Sealed format prevents institutional herding
• Aggregated forecast reflects diverse intelligence sources
• Each organization's predictions remain attributable for track record building
• Resolution based on defined outcome criteria

#Risks and Common Mistakes

Reveal failure penalties

Traders who commit but fail to reveal (intentionally or accidentally) face penalties, typically forfeiture of stakes or exclusion from future markets. Ensure you can complete the reveal phase before committing. Technical failures, forgotten secrets, or unavailability during the reveal window can be costly.

Secret management complexity

The commitment scheme requires storing the secret used in the hash. Losing this secret makes valid reveal impossible. Use secure, backed-up storage for secrets, especially for high-stakes commitments.

Timing coordination challenges

All participants must commit before anyone reveals. Coordinating global participants across time zones while enforcing deadlines creates operational complexity. Late commits are rejected; early reveals are impossible. Understand exact timing requirements.

Reduced price discovery

Traditional markets provide continuous price signals as traders update positions. Commit-reveal markets generate signals only at reveal time, potentially days or weeks of forecasting silence. For time-sensitive decisions, this delay may be problematic.

Gaming through multiple identities

Sophisticated actors might submit multiple commitments across different identities, planning to reveal only favorable ones. Platforms combat this through identity verification, stake requirements, and reveal-or-forfeit rules. Understand anti-gaming measures before assuming prediction independence.

Overconfidence in sealed format

The sealed format does not prevent systematic biases; all traders might independently reach the same wrong conclusion. Independence prevents herding but not correlated errors from shared information sources or common analytical frameworks.

Strategic non-reveal

If a trader commits but learns before reveal that their prediction is likely wrong, they face a choice: reveal and score poorly, or forfeit the stake. If forfeit is cheaper than expected loss, non-reveal becomes strategic. Platforms design penalty structures to discourage this.

#Practical Tips for Traders

• Secure your commitment secrets immediately. The moment you commit, store the secret in multiple secure locations. Lost secrets mean forfeited stakes regardless of prediction quality.

• Set calendar reminders for reveal deadlines. Missing the reveal window wastes all analytical effort. Build buffer time before deadlines for technical issues.

• Develop independent analytical frameworks. Commit-reveal markets reward truly independent analysis. If your process relies heavily on public consensus or visible forecasts, the sealed format provides no advantage.

• Calibrate probability estimates carefully. Proper scoring rules reward calibration: predicting 70% on events that happen 70% of the time. Overconfidence destroys expected value even when directionally correct.

• Consider the commitment deadline strategically. Earlier commitment means more time for new information to emerge before resolution. Later commitment incorporates more information but may still miss important developments after commit.

• Track your sealed versus open market performance. Compare accuracy in commit-reveal markets to open trading. Significant differences reveal whether social information helps or hurts your forecasting.

• Verify platform commitment mechanics. Understand exactly how the platform generates and verifies commitments. Some use client-side hashing; others use server-side sealing. Security properties differ.

#Related Terms

• Opportunity Market
• Information Aggregation
• Price Discovery
• Sharp Money
• Market Manipulation
• Oracle
• Binary Market
• Resolution Criteria

#FAQ

#What is a commit-reveal market?

A commit-reveal market is a prediction market using a two-phase structure to prevent herding. In the commit phase, traders submit cryptographically sealed predictions that cannot be read by others. In the reveal phase, after all commitments are locked, traders reveal their actual predictions. The platform verifies each reveal matches its commitment. This ensures all predictions are made independently; no trader can see or react to others' forecasts before committing their own, eliminating copycat behavior and social influence.

#How does commit-reveal prevent herding?

Herding occurs when traders observe and follow others' predictions rather than thinking independently. In open markets, early movers influence later traders, potentially cascading errors. Commit-reveal breaks this by making all predictions during the commit phase while no predictions are visible. When reveals occur simultaneously, it is too late to change positions. Each trader must rely solely on their own analysis. The aggregate forecast thus reflects n independent opinions rather than variations on the first few visible predictions.

#What happens if I don't reveal my prediction?

Failing to reveal typically triggers penalties specified by the platform. Common consequences include: forfeiture of committed stake, exclusion from payout distribution, negative impact on reputation scores, or temporary/permanent ban from future markets. The penalty structure is intentionally punitive to prevent strategic non-reveal, where traders might otherwise hide predictions they expect to score poorly. Before committing, ensure you can reliably complete the reveal phase (lost secrets, technical issues, or scheduling conflicts can cause unintentional forfeitures).

#Are commit-reveal markets better than traditional prediction markets?

Each structure has advantages. Commit-reveal markets excel at extracting independent forecasts, preventing manipulation through visible positioning, and enabling honest expression of uncertain or contrarian views. Traditional markets provide continuous price discovery, allow position adjustment as information evolves, and create real-time signals for decision-makers. Commit-reveal works best for aggregating expert forecasts on discrete events; traditional markets work best for liquid, continuous trading with dynamic information incorporation. Many forecasting applications benefit from both approaches.

#How do payouts work in commit-reveal markets?

Payouts typically use proper scoring rules that reward both accuracy and calibration. Common approaches include Brier scoring (based on squared error between prediction and outcome) and logarithmic scoring (which heavily penalizes confident wrong predictions). A pool of funds is distributed among participants proportionally to their scores. Better predictions earn larger shares. Some platforms also incorporate reputation systems where consistent accuracy increases future payout weights. The specific scoring rule significantly affects optimal prediction strategy, so verify platform rules before participating.