Risk Management

Correlated Betting Streaks and Risk of Ruin: A Martingale Analysis

Summary by Robert Gorak · Published July 22, 2026 · Last reviewed July 22, 2026

Vladimir Pozdnyakov·2025·arXiv Working Paper

The gambler's ruin problem calculates the probability a series of correlated bets drives an account to zero before reaching a target gain. Pozdnyakov (2025), in "Martingale Approach to Gambler's Ruin Problem for Correlated Random Walks," solves this with martingales and the Optional Stopping Theorem. For a fair-coin game betting HH against TH, the ruin probability of reaching $1 before losing $1 is .25. The expected number of bets until ruin equals 2AB+B-A+1 for this game.

What the Study Found

In the HH vs. TH game, the expected number of occurrences of each pattern in n coin flips is (n - 1)/4. The expected waiting time until the first HH is 6 flips, versus 4 flips for the first TH. The expected waiting time until the first occurrence of either pattern is 3 flips. For a symmetric correlated random walk with p = q = 1/2, the ruin probability reduces to α = B/(A + B). The HH vs. TH ruin probability formula, α = (B - 1/2)/(A + B), yields α = .25 when A equals B equals 1.

Methodology

This is a theoretical paper with no empirical dataset, sample size, or time period. The methodology is mathematical derivation using the Optional Stopping Theorem applied to martingales built for two-state and three-state Markov chains representing correlated random walks. Illustrative examples include a fair-coin game betting on the patterns HH and TH, and a three-state Markov chain with transition probabilities 1/2, 1/3, and 1/8.

Key Statistics

Metric Finding Context
Ruin probability, HH vs. TH game α = (B - 1/2)/(A + B) Fair-coin two-pattern game; A, B = dollar targets
Expected duration, HH vs. TH game E(τ) = 2AB + B - A + 1 Fair-coin two-pattern game
Ruin probability, symmetric CRW α = (B - 1 + 1/(2(1-p))) / (A + B - 2 + 1/(1-p)) Two-state CRW with increments {1,-1}, p = q
Expected duration, symmetric CRW E(τ) = AB(1-p)/p + (A+B)(2p-1)/(2p) Two-state CRW with increments {1,-1}, p = q
Probability HH occurs before TH .25 Fair coin, unconditional
Expected wait until first HH 6 flips Fair coin
Expected wait until first TH 4 flips Fair coin

Why This Matters

Trading streaks are correlated, not independent, so risk-of-ruin math built on i.i.d. assumptions can misstate the true odds of blowing up an account. The martingale technique lets risk managers compute exact ruin probabilities and expected time to ruin under serial correlation. The delay framework can also model position-sizing rules that sometimes skip a bet instead of always wagering. Open questions remain for random walks with more than three states, limiting use in finer-grained risk models.

Frequently Asked Questions

A .25 probability of reaching $1 before losing $1 illustrates the gambler's ruin problem for correlated random walks, per Pozdnyakov (2025). The method applies martingales and the Optional Stopping Theorem to two- and three-state Markov chains representing win/loss sequences, extending the classical i.i.d. gambler's ruin problem.

A ruin probability of α=(B-1/2)/(A+B) applies to a fair-coin game betting HH against TH, per Pozdnyakov (2025). The paper builds exponential and quadratic martingales to solve ruin probabilities and expected duration for two- and three-state correlated Markov chains, including versions with delays.

E(τ)=AB(1-p)/p+(A+B)(2p-1)/(2p) is the expected steps to ruin, per Pozdnyakov (2025). The formula applies to a symmetric correlated random walk with increments {1,-1} and reduces to the classical i.i.d. result E(τ) = AB at p = 1/2, matching the independent-bet case.

A symmetric correlated random walk with p=q≠1/2 has ruin probability α=(B-1+1/(2(1-p)))/(A+B-2+1/(1-p)), unlike the i.i.d. formula α=B/(A+B), per Pozdnyakov (2025). Serial correlation in the win/loss sequence shifts the true odds of ruin relative to independent-bet models. The boundaries A and B stay fixed; only the correlation structure changes the answer.

Source

Vladimir Pozdnyakov (2025). Martingale Approach to Gambler's Ruin Problem for Correlated Random Walks. arXiv Working Paper.

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