https://www.sarem-seitz.com/winning-with-simple-not-even-linear-time-series-models

simple_forecast.py

full_sample = [] 

np.random.seed(123)

for i in range(10000):
    draw = np.random.choice(diffed_s,len(test))
    result = list(diffed.iloc[-12:].values)

    for t in range(len(test)):
        result.append(result[t]+draw[t])

    full_sample.append(np.array(((rooted.iloc[-1])+np.cumsum(result[12:]))**2).reshape(-1,1))

    
reshaped = np.concatenate(full_sample,1)
result_mean = np.mean(reshaped,1)
lower = np.quantile(reshaped,0.05,1)
upper = np.quantile(reshaped,0.95,1)


plt.figure(figsize = (14,8))
plt.plot(train, label = "Train",color="blue")
plt.plot(test, label = "Test",color="red")
plt.grid(alpha = 0.5)

plt.plot(test.index, result_mean,label = "Simple model forecast",color="green")
plt.legend()
plt.fill_between(test.index,lower,upper,alpha=0.3,color="green")