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Euler–Maruyama Scheme and Coefficient Conditions — Examples

1 · Prerequisites

2 · Summary

Objective

The first example computes the grid recursion and continuous interpolation for a scalar additive-noise equation with an exact path and finite moments. The second checks a superlinear drift against the global Lipschitz and linear-growth hypotheses, showing precisely why the uniform-moment theorem does not apply.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-6-luna)Open item page →

Euler–Maruyama for a constant-coefficient additive-noise equation

Facts & Assumptions

Given: AC, T=1, h=1/n for an integer n≥1, and X0=0. Work on a complete filtered probability space whose filtration is right-continuous and contains every null subset in F0. Let W be a scalar standard Brownian motion adapted to this filtration, with Wt−Ws independent of Fs for every 0≤s<t≤1. Take b(t,x)=1 and σ(t,x)=1.

[F1]

The Euler–Maruyama step is Yk+1=Yk+b(tk,Yk)h+σ(tk,Yk)ΔWk. Euler–Maruyama recursion

[F2]

On [tk,tk+1], the interpolation is Yt=Yk+b(tk,Yk)(t−tk)+σ(tk,Yk)(Wt−Wtk). Euler–Maruyama step process and continuous interpolation

[F3]

The uniform-moment theorem bounds sup⁡t≤TE∣Yt∣p whenever E∣X0∣p<∞. Euler–Maruyama uniform moments and interpolation increments

[F4]

The Itô integral of the constant integrand 1 equals the Brownian increment. Ito integral for square-integrable predictable processes

[F5]

A strong solution is an adapted continuous process satisfying the finite-coordinate Itô equation indistinguishably. Itô SDE data and strong solution

[F6]

The finite-energy Itô-integral process has a continuous martingale version, and any two such continuous versions agree at all times on a measurable probability-one event. The Ito integral process has a continuous martingale version

[A1]

AC is inherited from the Brownian-motion and Itô-integral interfaces; the explicit calculation below makes no choice. The Axiom of Choice

Example

Consider the scalar additive-noise equation dXt=dt+dWt on [0,1]. The coefficients are constant, and for each n the uniform mesh has n steps of length h=1/n.

Verification

1.1givenalgebra

The functions b=1 and σ=1 are jointly Borel, globally Lipschitz in state with constant 0, and satisfy the stated linear-growth bound with a finite K. Their time increments vanish, so the required half-Hölder time modulus holds. The deterministic initial value X0=0 is F0-measurable, independent of future Brownian increments, and has every finite moment.

1.2F1F2F4F5F6algebra

From [F1], induction gives Yk=kh+Wkh. Substituting the coefficients into [F2] gives Yt=kh+(t−kh)+Wkh+Wt−Wkh=t+Wt on every interval. By [F4], at every fixed time the candidate path Xt=t+Wt satisfies the integral equation. The continuous-version theorem [F6] and equality at all rational times identify these processes indistinguishably; hence [F5] makes this adapted continuous candidate a strong solution. Any strong solution with the same data equals t+Wt directly from the constant-coefficient equation, so this is the exact path.

2.1A1F3step 1.2algebra∎

The initial value X0=0 has every finite moment. Applying [F3] for each finite p≥2 therefore proves finite moments of the grid, step, and interpolated processes uniformly in n and t≤1. The explicit identity Yt=t+Wt from step 1.2 also identifies the exact path. AC in [A1] is inherited from the cited interfaces; no choice enters these computations.

ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-6-luna)Open item page →

A superlinear drift outside the Euler–Maruyama moment contract

Facts & Assumptions

Given: AC, a scalar state, a scalar Brownian increment, and the coefficient pair b(x)=−x3, σ(x)=1.

[F1]

The shared contract requires globally Lipschitz coefficients in state and a uniform linear-growth bound. Euler–Maruyama recursion

[F2]

The uniform-moment theorem applies only under the coefficient and initial-value hypotheses of the shared contract. Euler–Maruyama uniform moments and interpolation increments

[A1]

AC is inherited from the Brownian interface; no choice is made in the coefficient calculation. The Axiom of Choice

Example

For the scalar coefficient pair b(x)=−x3 and σ(x)=1, the drift is superlinear: its magnitude grows faster than 1+∣x∣. This is an example about the hypotheses of the Euler–Maruyama moment theorem; it makes no claim about strong existence, instability, or convergence for this particular equation.

Verification

1.1F1algebra

The diffusion σ=1 is globally Lipschitz and has linear growth. For the drift, ∣b(x)∣/(1+∣x∣)=∣x∣3/(1+∣x∣)→∞ as ∣x∣→∞, so no finite linear-growth constant exists. Also ∣b(x)−b(0)∣/∣x∣=∣x∣2→∞, so no finite global Lipschitz constant exists.

2.1A1F1F2algebra∎

Since both required drift conditions fail, the uniform-moment theorem [F2] cannot be invoked for this coefficient pair. The conclusion is only that its stated hypotheses are absent; no contrary convergence or moment claim follows. AC in [A1] is inherited and no choice is used.

Sources