How to numerically simulate exponential stochastic integral

Question

For example given an integral

$$ \int^t_0 \exp(aW(t'))\,dt', t\in\mathbb R_+ $$ where $W(t')$ is a standard Wiener process.

I've been very confused about stochastic integrals like $\int^t_0 W(t')\,dt'$, for example here Integral of Brownian motion w.r.t. time

My question is how to numerically simulate this integral (i.e. simulate trajectories with evolution of time)

Answer 1

making use of this formula :

$$ y(t_{k+1}) = y({t_k}) + \int^{t_{k+1}}_{t_k} y(t) dt $$

Let's define $F$ as: $$ F(t)=\int^t_0 \exp(aW(t'))\,dt', \forall t\in\mathbb R_+\\ dF(t)=\exp(aW(t))dt $$

1. Choose a small $\Delta t$.
2. Simulate $\Delta W\sim \mathcal N(0,\Delta t)$
3. Calculate $W(t+\Delta t)=W(t) + \Delta W$
4. Calculate $F(t+\Delta t)=F(t)+ \exp(aW(t))\Delta t $
5. Repeat 2, 3 and 4 as many times as you want.

Answer 2

@ThomasG's solution is implemented in python (give or take some care with the zero index) as:

import numpy as np

dt = 1e-2; j = 10; a = 1

dW = np.random.randn(j+1); dW[0] = 0
W = np.cumsum(dW)
F = np.cumsum(np.exp(a * W) * dt)