Temporal Ambiguity in Timezone Disputes for Event Markets

Executive Summary

In event markets such as Polymarket and Kalshi, temporal ambiguity, particularly related to timezones, can lead to significant disputes over the settlement of outcomes. This article delves into how such disputes arise, their impact on resolution risk, and how the SettleRisk API can be used to assess and mitigate these risks.

Core Concept

Temporal ambiguity refers to the uncertainty stemming from the lack of clarity regarding the specific time an event occurs or is reported. In the context of event markets, this often revolves around timezone discrepancies. For instance, an event's occurrence might be reported in a different timezone than where the market participants are located, leading to confusion over the exact timing and thus the settlement outcome.

The SettleRisk API quantifies resolution risk by scoring it on a scale from 0 to 100, categorizing it into LOW, MEDIUM, HIGH, and CRITICAL tiers. This scoring is based on a deterministic, closed-form scoring model with four version stamps and a 15-driver taxonomy. One of these drivers is specifically designed to account for temporal ambiguity.

Worked Example

Let's consider a market on Kalshi regarding a geopolitical event that is expected to occur at a specific time in a particular timezone. The market is structured such that a payout is triggered if the event occurs before a certain date. Due to temporal ambiguity, there may be disputes if the event's timing is reported differently across various sources.

To handle this, we can use the SettleRisk API to score the resolution risk. Here's how you can do it using the Python and TypeScript SDKs:

Python SDK Example

from settlerisk import SettleRiskClient

# Initialize the client
client = SettleRiskClient("your_api_key")

# Fetch the resolution risk score for a given market
market_id = "geopolitical_event_123"
score = client.get_resolution_risk_score(market_id)

# Print the score and its category
print(f"Resolution Risk Score: {score['score']} - {score['category']}")

TypeScript SDK Example

import { SettleRiskClient } from "settlerisk";

// Initialize the client
const client = new SettleRiskClient("your_api_key");

// Fetch the resolution risk score for a given market
const marketId = "geopolitical_event_123";
client.getResolutionRiskScore(marketId).then(score => {
  console.log(`Resolution Risk Score: ${score.score} - ${score.category}`);
});

Implementation Notes

When implementing the SettleRisk API, it’s crucial to consider the following:

1. Market Parameters: Ensure that the market parameters are correctly set, including the timezone details and the exact wording that could lead to temporal ambiguity.
2. Driver Attribution: Utilize the 15-driver taxonomy to understand which factors are contributing most to the resolution risk score.
3. Version Stamps: Be aware of the version stamps on the scoring model to handle updates and changes in the risk assessment methodology.

Failure Modes

A key failure mode in handling temporal ambiguity is underestimating the impact of timezone discrepancies on the resolution risk. This can lead to incorrect risk assessments and pricing, potentially resulting in financial losses.

Checklist

• Verify the timezone of the event report against the market's conditions.
• Use SettleRisk API to score resolution risk, focusing on the temporal ambiguity driver.
• Regularly update the SettleRisk client SDK to incorporate any changes in the scoring model.
• Monitor market conditions and adjust risk assessments accordingly.

Sources + Further Reading

For a deeper understanding of how temporal ambiguity affects resolution risk, refer to the following resources:

• SettleRisk Methodology: Learn more about the deterministic scoring model.
• Features of SettleRisk: Understand the 15-driver taxonomy and its implications.
• Pricing Engine Outputs: Explore how risk scores translate into pricing.

By leveraging the SettleRisk API, market participants can better manage the risks associated with temporal ambiguity in timezone disputes, ensuring a more robust and reliable trading strategy in event markets.