Cross-Platform Arbitrage: Leveraging SettleRisk for Polymarket and Kalshi Pricing

Executive Summary

In the fast-paced world of prediction markets, cross-platform arbitrage is an essential strategy for traders to maximize profits. SettleRisk's API offers a resolution risk scoring and dispute pricing tool that is pivotal in this domain. This deep dive will analyze how SettleRisk facilitates arbitrage opportunities between Polymarket and Kalshi by providing comparative risk scores, settlement delay modeling, and pricing insights.

Core Concept

Cross-platform arbitrage involves exploiting price discrepancies between different prediction market platforms. Polymarket and Kalshi, as two leading platforms, offer traders a rich ground for such strategies. The core concept revolves around the resolution risk scoring model provided by SettleRisk, which assigns a risk score ranging from 0 to 100 to each market outcome. This score is then used to calculate the risk premium, capital lockup cost, and fair spread.

Quantitative Framework

The determination of resolution risk can be mathematically represented as follows:

Resolution Risk Score = f(Driver1, Driver2, ..., Driver15)

Where f is a deterministic function based on our 15-driver taxonomy. Each driver is attributed a weight based on historical data and market behavior, and the scores are combined to yield a final risk score.

Worked Example

Let's consider a scenario where a trader identifies a discrepancy in resolution risk between Polymarket and Kalshi for an event related to a geopolitical issue. Using SettleRisk's API, they can fetch the risk scores for the same event on both platforms.

Python SDK Code Example

from settlerisk import SettleRiskClient

# Initialize SettleRisk client
client = SettleRiskClient(api_key="your_api_key")

# Fetch risk score for Polymarket
polymarket_risk_score = client.get_risk_score(platform="polymarket", event_id="event123")

# Fetch risk score for Kalshi
kalshi_risk_score = client.get_risk_score(platform="kalshi", event_id="event123")

print(f"Polymarket Risk Score: {polymarket_risk_score}")
print(f"Kalshi Risk Score: {kalshi_risk_score}")

TypeScript SDK Code Example

import { SettleRiskClient } from "settlerisk";

// Initialize SettleRisk client
const client = new SettleRiskClient({ apiKey: "your_api_key" });

// Fetch risk score for Polymarket
client.getRiskScore({ platform: "polymarket", eventId: "event123" })
  .then(polymarketRiskScore => console.log(`Polymarket Risk Score: ${polymarketRiskScore}`))
  .catch(error => console.error(error));

// Fetch risk score for Kalshi
client.getRiskScore({ platform: "kalshi", eventId: "event123" })
  .then(kalshiRiskScore => console.log(`Kalshi Risk Score: ${kalshiRiskScore}`))
  .catch(error => console.error(error));

Implementation Notes

When implementing cross-platform arbitrage strategies, consider the following:

1. Platform Bases: Polymarket and Kalshi have different bases for their markets, which impacts the direct comparability of prices and risk scores.
2. Settlement Delays: Settlement delays are lognormally distributed, and understanding the p50, p90, and p99 values can significantly affect your arbitrage strategy.
3. API Rate Limits: Be mindful of API rate limits when fetching large volumes of data for real-time trading decisions.

Markdown Table: Settlement Delay Distribution

| Platform | p50 (days) | p90 (days) | p99 (days) | |----------|-----------|-----------|-----------| | Polymarket | 2.5 | 5.1 | 10.2 | | Kalshi | 3.0 | 6.2 | 12.5 |

Failure Modes

Failing to account for the differences in resolution risk scoring between platforms can lead to incorrect pricing assumptions and missed arbitrage opportunities. Additionally, relying solely on historical data without considering current market dynamics can result in outdated risk assessments.

Checklist

• Verify API keys and access permissions for both Polymarket and Kalshi.
• Understand and account for platform-specific bases and resolution rules.
• Monitor API rate limits to ensure uninterrupted data flow.
• Regularly update your risk models based on the latest market data and trends.

Sources + Further Reading

For a deeper understanding of resolution risk and how it impacts arbitrage, refer to our methodology and pricing pages. To explore the API's capabilities further, check out our docs and demo. For a comparative analysis of risk across platforms, visit our compare section.

By leveraging SettleRisk's API, traders can navigate the complex landscape of cross-platform arbitrage with confidence, capitalizing on price discrepancies and minimizing risk exposure.