Cross-Platform Arbitrage: Pricing Insights from Polymarket and Kalshi

Executive Summary

In today's rapidly evolving world of prediction markets, cross-platform arbitrage presents a lucrative opportunity for traders. This deep dive explores the intricacies of arbitrage between Polymarket and Kalshi, two prominent platforms in the space. We'll utilize SettleRisk's API to score resolution risk and determine pricing, providing a practical framework for traders to capitalize on discrepancies between these platforms.

Core Concept

Cross-platform arbitrage involves taking advantage of price differences between markets on different prediction platforms. The core concept revolves around buying a contract on one platform and selling it on another, aiming to lock in a risk-free profit. However, this simplicity masks the complexities involved in assessing resolution risk accurately.

Resolution Risk Scoring Model: To score resolution risk, we use a deterministic, closed-form model: [ \text{Risk Score} = \sum_{i=1}^{15} w_i \times f_i(x_i) ] where ( w_i ) are weights for each of the 15 risk drivers, and ( f_i(x_i) ) are the functions mapping each driver's value to a risk score contribution.

Worked Example

Let's consider a hypothetical scenario where the same event is listed on both Polymarket and Kalshi but with different prices.

Step 1: Retrieve Market Data

• Use SettleRisk's API to fetch data for the same event from both platforms.

Python SDK Example:

from settlerisk import SettleRiskClient

client = SettleRiskClient("YOUR_API_KEY")
polymarket_data = client.get_market_data("POLYMARKET_EVENT_ID")
kalshi_data = client.get_market_data("KALSHI_EVENT_ID")

TypeScript SDK Example:

import { SettleRiskClient } from "settlerisk";

const client = new SettleRiskClient("YOUR_API_KEY");
const polymarketData = await client.getMarketData("POLYMARKET_EVENT_ID");
const kalshiData = await client.getMarketData("KALSHI_EVENT_ID");

Step 2: Score Resolution Risk

• Calculate the risk score for each market using the SettleRisk API.

Step 3: Determine Arbitrage Potential

• Use the risk scores to assess the potential for arbitrage.

Markdown Table: Risk Scores and Arbitrage Potential | Platform | Event ID | Risk Score | Buy/Sell | Arbitrage Potential | |----------|-----------|------------|----------|---------------------| | Polymarket | EVENT123 | 30 | Sell | High | | Kalshi | EVENT456 | 45 | Buy | High |

Step 4: Execute Trade

• Based on the risk scores and potential arbitrage, execute the trade.

Implementation Notes

• Ensure that the API keys used are valid and have the necessary permissions.
• Consider the transaction costs and liquidity constraints when executing trades.
• Keep abreast of any changes in platform rules that might affect resolution risk.

Failure Modes

• Oracle Failure: A failure in the data feed can lead to incorrect risk assessments.
• Platform-Specific Rules: Changes in platform rules can alter resolution risk unexpectedly.
• Market Volatility: Rapid price changes can erode arbitrage opportunities.

Checklist

1. Verify API keys and connectivity.
2. Fetch and compare market data from both platforms.
3. Score resolution risk accurately using SettleRisk.
4. Calculate arbitrage potential based on risk scores.
5. Execute trades with consideration of transaction costs.
6. Monitor for any changes in platform rules or market conditions.

Sources + Further Reading

For a deeper understanding of the mechanics behind SettleRisk's scoring model, refer to our methodology page. To explore the API's capabilities further, visit our documentation. For a detailed analysis of resolution risk in prediction markets, see our post on resolving ambiguity.