Event Horizon Decay Metric

Overview

This pillar analyzes the relationship between a market's timeframe and the stability of its key variables. It calculates an 'information decay' rate, helping you determine if a market is a predictable event or a long-term speculate.

What It Does

The Event Horizon Decay Metric models the expected half-life of critical information, like polling data or financial reports, relative to a market's resolution date. It assesses historical volatility and the frequency of disruptive events in the market's category. The pillar then generates a score indicating the likelihood that current conditions will be irrelevant by the market's close.

Why It Matters

It provides a crucial defense against overvaluing short-term signals in long-range markets. This pillar highlights when a market's current odds are built on a foundation of fleeting data, preventing costly mistakes based on temporary hype or momentum.

How It Works

First, the model identifies the market's resolution date and its primary information drivers. Second, it calculates the historical 'half-life' for those drivers using data from similar past markets. Finally, it combines the time to resolution with the information half-life to produce a decay score, which represents the risk of unforeseen changes.

Methodology

The core calculation is the Decay Score (DS), where DS = (Time to Resolution in Days / Information Half-Life) * Volatility Factor. 'Information Half-Life' is an estimated value based on historical data for the asset class (e.g., political polls, ~45 days; quarterly earnings, ~90 days). The 'Volatility Factor' is a 0.5-1.5 multiplier derived from historical price volatility or relevant indices.

Edge & Advantage

This pillar provides a quantitative framework for an often intuitive concept, giving you a clear signal to differentiate between a calculated risk and a pure gamble.

Key Indicators

• Information Half-Life

  high

  The estimated time it takes for current key information to lose half of its predictive value for a given market type.

• Regime Change Probability

  high

  The likelihood of a major, market-altering event occurring before the resolution date, based on historical precedent.

• Resolution Distance Score

  medium

  A normalized score from 1 to 100 based on the time remaining until the market resolves; higher scores mean more time for decay.

Data Sources

• Historical Market Data

  Provides odds movement and volatility data from past markets to calculate baseline decay rates.

• Academic Studies

  Research papers from political science, economics, and sociology that model information persistence.

Example Questions This Pillar Answers

• → Will the UK rejoin the European Union by 2035?
• → Will the global average temperature anomaly exceed 1.5°C for a full calendar year before 2030?
• → Will a specific candidate win the next presidential election two years from now?

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