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·4 min read·SettleRisk Team

Navigating Resolution Risk in Prediction Markets: A Guide for Traders

prediction-marketsresolution-risktrading-strategy

Introduction

In the rapidly evolving landscape of prediction markets, traders and market makers are continually seeking ways to manage and mitigate potential risks. One key aspect of this risk management is understanding and assessing resolution risk, which pertains to the likelihood of disputes arising post-settlement due to interpretation or definition issues of market resolutions. In this post, we will delve into the intricacies of resolution risk, dispute probabilities, and settlement delays through the lens of SettleRisk's scoring and pricing models, providing practical examples for traders using both Python and TypeScript SDKs.

Understanding Resolution Risk

Resolution risk in prediction markets is a measure of the uncertainty surrounding the final outcome of a market. This risk can significantly impact traders' positions, as disputes can lead to delays in settlement and affect the payout. SettleRisk categorizes resolution risk across four tiers:

  • LOW (0-20): Minimal risk of disputes.
  • MEDIUM (20-50): Moderate risk,需谨慎处理。
  • HIGH (50-75): High risk, potential for significant disputes.
  • CRITICAL (75-100): Extremely high risk, almost certain disputes.

Dispute Probability Calculation

SettleRisk calculates the dispute probability (p_dispute) using a proprietary formula that considers the resolution risk score, platform-specific factors, and criticality of the risk. The formula is as follows:

[ p_ = \text(0.01 + 0.003 \times \text + 0.05 \times I(\text) + 0.06 \times I(\text), 0, 0.90) ]

Where:

  • score is the resolution risk score assigned by SettleRisk.
  • I(\text{polymarket}) is an indicator function that equals 1 if the market is on Polymarket and 0 otherwise.
  • I(\text{CRITICAL}) is an indicator function that equals 1 if the score is CRITICAL and 0 otherwise.
  • clamp ensures the dispute probability stays within the [0, 0.90] range.

Settlement Delays

Settlement delays are modeled using a lognormal distribution, providing estimates for the 50th, 90th, and 99th percentiles in hours. These percentiles help traders gauge the expected time until resolution and manage their capital accordingly.

Pricing Engine Outputs

SettleRisk's pricing engine outputs several key metrics that help traders make informed decisions:

  • Risk Premium (bps): Additional basis points to account for resolution risk.
  • Capital Lockup Cost (bps): Cost associated with capital tied up due to potential delays.
  • Fair Spread (bps): Recommended spread to mitigate risk based on the resolution risk score.
  • Do-Not-Quote Flag: Indicates markets with extremely high risk that should be avoided.

Practical Application in SDKs

Python SDK Example

from settlerisk import SettleRiskClient

# Initialize the SettleRiskClient
client = SettleRiskClient(api_key="your_api_key_here")

# Fetch the resolution risk score for a specific market
market_id = "market_123"
score = client.get_score(market_id)

# Calculate dispute probability
p_dispute = 0.01 + 0.003 * score + 0.05 * (1 if "polymarket" in market_id else 0) + 0.06 * (1 if score >= 75 else 0)
p_dispute = min(max(p_dispute, 0), 0.90)

print(f"Resolution Risk Score: {score}, Dispute Probability: {p_dispute}")

TypeScript SDK Example

import { SettleRiskClient } from "settlerisk";

// Initialize the SettleRiskClient
const client = new SettleRiskClient({apiKey: "your_api_key_here"});

// Fetch the resolution risk score for a specific market
const marketId = "market_123";
client.getScore(marketId).then(score => {
    // Calculate dispute probability
    let pDispute = 0.01 + 0.003 * score + 0.05 * (marketId.includes("polymarket") ? 1 : 0) + 0.06 * (score >= 75 ? 1 : 0);
    pDispute = Math.min(Math.max(pDispute, 0), 0.90);

    console.log(`Resolution Risk Score: ${score}, Dispute Probability: ${pDispute}`);
});

Comparison of Platform Base Points

Below is a comparison table outlining the base points for Polymarket and Kalshi, which are used in the dispute probability formula:

| Platform | Base Points | |----------|------------| | Polymarket | 12 | | Kalshi | 8 |

Incorporating SettleRisk in Trading Strategies

Traders can incorporate SettleRisk's resolution risk scores and dispute probabilities into their trading strategies to manage risk effectively. For instance, a trader might avoid markets with a high dispute probability or adjust their position sizes based on the expected capital lockup time.

Conclusion

Understanding and managing resolution risk is crucial for traders and market makers in prediction markets. By leveraging SettleRisk's API, traders can score resolution risk, calculate dispute probabilities, and model settlement delays to make informed decisions. This post provided a detailed look into the mathematics behind these calculations and practical examples of how to implement these models using SettleRisk's SDKs.

For more information on how SettleRisk can enhance your trading strategies, explore our methodology, features, and pricing. To get started, sign up for a demo or sign up for an account.