The Volatility Tax: Ergodicity Breaking in Algorithmic Markets
Technical Paper

The Volatility Tax:
Sequence Risk & Ergodicity Breaking

Why "Average Returns" are a mathematical lie in High-Frequency Algorithmic Greyhound Markets.

Abstract

This interactive report defines the conflict between Ensemble Average (the market's theoretical return) and Time Average (a single trader's realized return). In "Non-Ergodic" systems like betting markets, a strategy can be profitable on average across 1,000 parallel universes, yet bankrupt a single trader in reality due to Sequence of Returns Risk.

?? Volatility Drag
? Sequence Risk
?? Non-Ergodicity
??? Kelly Criterion

1. The Ergodicity Conflict

In an Ergodic system, the average outcome of a group (Ensemble) is the same as the outcome of an individual over time. Betting markets are Non-Ergodic.

Explore the difference below. The Grey Lines represent the "Ensemble" (many traders). The Black Line is YOU. Notice how you can go bust even if the "average" trader survives.

Key Concept

Ensemble Average:
$\frac{1}{N} \sum x_i$
(Snapshot of everyone)

Time Average:
$\lim_{t \to \infty} \frac{1}{t} \sum x(t)$
(Your actual bankroll)

Simulated coin flips. 50% Win (+50%), 50% Loss (-40%). Expected Value is Positive (+5%), but Time Average is Negative (-10%).

2. The Volatility Tax (Gravity Well)

Losses are not linear; they are geometric. A 50% loss requires a 100% gain just to break even. This asymmetry creates a "Volatility Tax" that drags down compounded returns. In algorithmic betting, this is the Absorbing Barrier.

?? The Ruin Calculator

Required Recovery Gain

+25.0%
Manageable correction.
Formula: $Gain = \frac{1}{1 - Loss} - 1$
The Cliff Edge: Notice the exponential spike. Beyond 50% drawdown, the required return becomes statistically improbable in high-efficiency markets.

3. Sequence Risk in High-Velocity Markets

In Greyhound Lay Betting, races occur every 10 minutes. This high velocity compresses Sequence Risk. A traditional stock trader faces a bad year; an algo-bettor faces a "bad afternoon" that contains the same statistical variance.

  • The Early Luck Paradox: A bad sequence at the start of an algorithm's life is 5x more destructive to capital than the same sequence occurring after 1,000 bets.
  • Capital Sensitivity: If you lose 30% of your bankroll on Day 1, your stake size (and profit potential) shrinks immediately.

The 'Martingale' Trap

Many lay bettors attempt to fix Sequence Risk by "Chasing Losses" (Martingale). This creates Negative Skew.

Bet 1 (Lose): -$10
Bet 2 (Lose): -$20
Bet 3 (Lose): -$40
Liability: Exponential Risk

*In a non-ergodic world, the market can remain irrational longer than you can remain solvent.

4. Strategy Comparison Engine

Test the defenses. Run a simulation of 100 bets using different staking methods. Observe how they handle a randomized sequence of wins and losses.

Select Strategy:
Simulation Parameters
Starting Bank: $1,000
Win Rate: 55%
Events: 100 Races