# Trade using a simple strategy
def trade(S1, S2, window1, window2):

    # If window length is 0, algorithm doesn't make sense, so exit
    if (window1 == 0) or (window2 == 0):
        return 0

    # Compute rolling mean and rolling standard deviation
    ratios = S1/S2
    ma1 = ratios.rolling(window=window1,
                               center=False).mean()
    ma2 = ratios.rolling(window=window2,
                               center=False).mean()
    std = ratios.rolling(window=window2,
                        center=False).std()
    zscore = (ma1 - ma2)/std

    # Simulate trading
    # Start with no money and no positions
    money = 0
    countS1 = 0
    countS2 = 0
    for i in range(len(ratios)):
        # Sell short if the z-score is > 1
        if zscore[i] < -1:
            money += S1[i] - S2[i] * ratios[i]
            countS1 -= 1
            countS2 += ratios[i]
            #print('Selling Ratio %s %s %s %s'%(money, ratios[i], countS1,countS2))
        # Buy long if the z-score is < -1
        elif zscore[i] > 1:
            money -= S1[i] - S2[i] * ratios[i]
            countS1 += 1
            countS2 -= ratios[i]
            #print('Buying Ratio %s %s %s %s'%(money,ratios[i], countS1,countS2))
        # Clear positions if the z-score between -.5 and .5
        elif abs(zscore[i]) < 0.75:
            money += S1[i] * countS1 + S2[i] * countS2
            countS1 = 0
            countS2 = 0
            #print('Exit pos %s %s %s %s'%(money,ratios[i], countS1,countS2))


    return money