Markets: A Rigorous Course

3.6 Gambler's ruin

Core about 20 min

Motivation

Kelly bettors never go broke in theory because they bet a fraction of current wealth. Real traders often bet fixed amounts (one lot, a fixed rupee risk), and a fixed bet on finite capital can be ruined. The gambler's-ruin problem is the exact model.

Ruin probability#

Setup

A gambler's capital, in units of the bet, is a random walk Xn=a+∑i=1nξiX_n = a + \sum_{i=1}^{n}\xi_i on {0,1,…,N}\{0, 1, \dots, N\} with ξi=+1\xi_i = +1 w.p. pp and −1-1 w.p. q=1−pq = 1 - p, started at a∈{0,…,N}a \in \{0, \dots, N\} and stopped at τ=inf⁡{n:Xn∈{0,N}}\tau = \inf\{n : X_n \in \{0, N\}\}. Ruin is {Xτ=0}\{X_\tau = 0\}; NN is a target at which the gambler quits. Let ρ=q/p\rho = q/p and Pa=P(Xτ=0∣X0=a)P_a = P(X_\tau = 0 \mid X_0 = a).

Proposition 3.11ruin probability

Pa={ρa−ρN1−ρN,p≠q,1−aN,p=q.(3.16)P_a = \begin{cases}\dfrac{\rho^a - \rho^N}{1 - \rho^N}, & p \ne q,\\[2mm] 1 - \dfrac aN, & p = q.\end{cases} \tag{3.16}

Letting N→∞N \to \infty (no target): Pa→ρa=(q/p)aP_a \to \rho^a = (q/p)^a if p>qp > q, and Pa→1P_a \to 1 if p≤qp \le q.

Proof 1difference equation

Conditioning on the first step, Pa=pPa+1+qPa−1P_a = pP_{a+1} + qP_{a-1} for 0<a<N0 < a < N, with P0=1P_0 = 1, PN=0P_N = 0. Try Pa=λaP_a = \lambda^a: pλ2−λ+q=0p\lambda^2 - \lambda + q = 0, whose roots are λ=1\lambda = 1 and λ=q/p\lambda = q/p (their product is q/pq/p and λ=1\lambda = 1 is a root since p+q=1p + q = 1). For p≠qp \ne q the roots are distinct, so Pa=A+BρaP_a = A + B\rho^a. The boundary conditions give A+B=1A + B = 1 and A+BρN=0A + B\rho^N = 0, so B=1/(1−ρN)B = 1/(1 - \rho^N), A=−ρN/(1−ρN)A = -\rho^N/(1 - \rho^N), which is (3.16). For p=qp = q the root 1 is double, Pa=A+BaP_a = A + Ba, and the boundary conditions give 1−a/N1 - a/N. The limits as N→∞N \to \infty: if ρ<1\rho < 1, ρN→0\rho^N \to 0; if ρ>1\rho > 1, divide numerator and denominator by ρN\rho^N to get (ρa−N−1)/(ρ−N−1)→1(\rho^{a-N} - 1)/(\rho^{-N} - 1) \to 1; if ρ=1\rho = 1, 1−a/N→11 - a/N \to 1.

Proof 2optional stopping

Mn=ρXnM_n = \rho^{X_n} is a martingale: E[ρXn+1∣Xn]=ρXn(pρ+qρ−1)=ρXn(q+p)=ρXnE[\rho^{X_{n+1}} \mid X_n] = \rho^{X_n}(p\rho + q\rho^{-1}) = \rho^{X_n}(q + p) = \rho^{X_n}. The stopping time τ\tau is a.s. finite: from any state, NN consecutive up-steps end the game, so P(τ>kN)≤(1−pN)k→0P(\tau > kN) \le (1 - p^N)^k \to 0. The stopped process Mn∧τM_{n\wedge\tau} is bounded (by max⁡(1,ρN)\max(1, \rho^N)), so optional stopping applies: ρa=E[ρXτ]=Paρ0+(1−Pa)ρN\rho^a = E[\rho^{X_\tau}] = P_a\rho^0 + (1 - P_a)\rho^N. Solve for PaP_a.∎

Expected duration#

Proposition 3.12expected duration

Da=E[τ∣X0=a]D_a = E[\tau \mid X_0 = a] is

Da=aq−p−Nq−p⋅1−ρa1−ρN(p≠q),Da=a(N−a)(p=q).(3.17)D_a = \frac{a}{q-p} - \frac{N}{q-p}\cdot\frac{1 - \rho^a}{1 - \rho^N} \quad (p \ne q), \qquad D_a = a(N - a) \quad (p = q). \tag{3.17}
Proof

Da=1+pDa+1+qDa−1D_a = 1 + pD_{a+1} + qD_{a-1}, D0=DN=0D_0 = D_N = 0. A particular solution of the inhomogeneous equation is Da=a/(q−p)D_a = a/(q - p) (check: 1+p(a+1)/(q−p)+q(a−1)/(q−p)=1+(a+p−q)/(q−p)=a/(q−p)1 + p(a+1)/(q-p) + q(a-1)/(q-p) = 1 + (a + p - q)/(q-p) = a/(q-p)). The general solution adds A+BρaA + B\rho^a; the boundary conditions give A=−BA = -B and B=N/((q−p)(1−ρN))B = N/((q-p)(1 - \rho^N)), which yields (3.17). For p=qp = q, a particular solution is −a2-a^2, and Da=−a2+A+BaD_a = -a^2 + A + Ba with the boundary conditions gives a(N−a)a(N - a). Alternatively, Xn−(p−q)nX_n - (p - q)n is a martingale, and optional stopping (justified since Eτ<∞E\tau < \infty) gives (p−q)Da=E[Xτ]−a=N(1−Pa)−a(p-q)D_a = E[X_\tau] - a = N(1 - P_a) - a.∎

Ruin with and without an edge#

Worked example 3.6.1roulette

On a European roulette wheel a bet on red wins with probability 18/37=0.486518/37 = 0.4865. A player with 10 units who stops at 20 is ruined with probability P10=0.632P_{10} = 0.632; the game lasts 97.7 spins on average. With 50 units and a target of 100, ruin probability rises to 0.937. Against a negative edge, small bets lose more surely than large ones: the law of large numbers works for the house. (Bold play, one bet of everything, minimises ruin probability in a subfair game; Dubins & Savage 1965.)

Worked example 3.6.2a trader with an edge

A trader wins 55% of fixed-size bets at even money. With capital of 5 bets and no target, ruin probability is (0.45/0.55)5=0.367(0.45/0.55)^5 = 0.367. With 20 bets, 0.018. If the edge is only 51%: 0.449 with 20 bets, 0.018 with 100 bets. Ruin probability decays geometrically in capital measured in bet units, at a rate set by the edge. A thin edge needs deep capital.

Practitioner notes

  • "Capital in bet units" is the variable that matters. A ₹2 lakh account trading one Nifty futures lot (contract value about ₹15.6 lakh at 24,000 × 65, as of Nov 2026) with a 1% stop risks ₹15,600 per trade: about 13 units of risk. That is a small aa.
  • In a subfair game (p<qp < q), ruin is certain without a target, and expected time to ruin from aa units is a/(q−p)a/(q - p) (let N→∞N \to \infty in (3.17)). Transaction costs turn many zero-edge strategies into subfair games (3.10.4).

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