asset.py

import random
import json

Y0 = 100
noise = lambda: random.gauss(0, 0.01)

def run(steps):
    y = [Y0] * steps
    for t in range(1, steps):
        y[t] = y[t-1] * (1 + noise())
    return y

if __name__ == '__main__':
    steps = 60
    runs = 10000
    data = [run(steps) for _ in range(runs)]
    with open("asset.json", "w") as f:
        json.dump(data, f)