Machine Learning, Deep Learning, Trading, Finance, Stock Market.
STEP): try: o = openp[i:i+WINDOW] h = highp[i:i+WINDOW] l = lowp[i:i+WINDOW] c = closep[i:i+WINDOW] v = volumep[i:i+WINDOW] volat = volatility[i:i+WINDOW] y_i = volatility[i+WINDOW+FORECAST] x_i = np.column_stack((volat, o, h, l, c, v)) We will take the same neural network architecture as above,