from apply_integrated_macd_poly_filter import apply_integrated_macd_poly_filter f, axarr = plt.subplots(3, 2) with open('jpm_trades.csv', 'r') as trades_csv: trades = np.array(list(csv.reader(trades_csv))[1:]).astype('double') prices = trades[:, 1] Nwindow = len(prices) # a) Delayed impulse Ndelay = 32 lag = 0 y_fde = apply_delayed_impulse_filter(prices, Ndelay) h_delta = delta(Ndelay, Nwindow) candidate = np.convolve(prices, h_delta) y_convolution = candidate[:len(prices)] x_axis = np.arange(Ndelay, len(prices)) axarr[0, 0].set_title("Ideal delay") axarr[0, 0].plot(x_axis, y_fde[Ndelay:]) axarr[0, 0].plot(x_axis, y_convolution[Ndelay:], 'o', markerfacecolor='none') # b) Box
from apply_delayed_impulse_filter import apply_delayed_impulse_filter from apply_integrated_macd_poly_filter import apply_integrated_macd_poly_filter f, axarr = plt.subplots(3, 2) Nwindow = 256 # a) Delayed impulse Ndelay = 32 lag = 0 impulse = np.zeros(Nwindow) impulse[lag] = 1 candidate = apply_delayed_impulse_filter(impulse, Ndelay) impulse_response_fde = candidate[lag:] impulse_response_direct = delta(Ndelay, Nwindow) axarr[0, 0].set_ylim(0, 1.1) axarr[0, 0].set_title("Ideal delay") axarr[0, 0].plot(impulse_response_fde) axarr[0, 0].plot(impulse_response_direct, 'o', markerfacecolor='none') # b) Box Nbox = 32 lag = 1 impulse = np.zeros(Nwindow) impulse[lag] = 1
from apply_integrated_macd_poly_filter import apply_integrated_macd_poly_filter f, axarr = plt.subplots(3, 2) Nwindow = 256 # a) Delayed impulse Ndelay = 32 lag = 0 impulse = np.zeros(Nwindow) impulse[lag] = 1 candidate = apply_delayed_impulse_filter(impulse, Ndelay) impulse_response_fde = candidate[lag:] impulse_response_direct = delta(Ndelay, Nwindow) axarr[0, 0].set_ylim(0, 1.1) axarr[0, 0].set_title("Ideal delay") axarr[0, 0].plot(impulse_response_fde) axarr[0, 0].plot(impulse_response_direct, 'o', markerfacecolor='none') # b) Box Nbox = 32 lag = 1 impulse = np.zeros(Nwindow) impulse[lag] = 1
f, axarr = plt.subplots(3, 2) with open('jpm_trades.csv', 'r') as trades_csv: trades = np.array(list(csv.reader(trades_csv))[1:]).astype('double') prices = trades[:,1] Nwindow = len(prices) # a) Delayed impulse Ndelay = 32 lag = 0 y_fde = apply_delayed_impulse_filter(prices, Ndelay) h_delta = delta(Ndelay, Nwindow) candidate = np.convolve(prices, h_delta) y_convolution = candidate[:len(prices)] x_axis = np.arange(Ndelay, len(prices)) axarr[0, 0].set_title("Ideal delay") axarr[0, 0].plot(x_axis, y_fde[Ndelay:]) axarr[0, 0].plot(x_axis, y_convolution[Ndelay:], 'o', markerfacecolor='none') # b) Box Nbox = 32 lag = 1