Pattern_Engulfing.py

# Base parameters
expected_cost    = 0.5 * (lot / 10000) 
assets           = asset_list(1) 
window           = 1000

# Trading parameters   
horizon          = 'H1'

# Mass imports 
my_data = mass_import(0, horizon)

# Defining the minimum width of the candle
body = 0.0005
def signal(Data, body):
    for i in range(len(Data)):        
       # Bullish Engulfing
       if Data[i, 3] > Data[i, 0] and Data[i - 1, 3] < Data[i - 1, 0] and (Data[i, 3] - Data[i, 0]) >= body and \
           Data[i, 1] > Data[i - 1, 1] and Data[i, 2] < Data[i - 1, 2] and Data[i, 3] > Data[i - 1, 0] and \
               Data[i, 0] < Data[i - 1, 3]:
                Data[i, 6] = 1        
       # Bearish Engulfing
       if Data[i, 3] < Data[i, 0] and Data[i - 1, 3] > Data[i - 1, 0] and (Data[i, 3] - Data[i, 0]) >= body and \
           Data[i, 1] < Data[i - 1, 1] and Data[i, 2] > Data[i - 1, 2] and Data[i, 3] < Data[i - 1, 0] and \
               Data[i, 0] > Data[i - 1, 3] :
               Data[i, 7] = -1


           
##############################################################################   1

my_data = adder(my_data, 10)
my_data = rounding(my_data, 4)
signal(my_data, body)

if sigchart == True:
    signal_chart_ohlc_color(my_data, assets[0], 3, 6, 7, window = 250)

holding(my_data, 6, 7, 8, 9)
my_data_eq = equity_curve(my_data, 8, expected_cost, lot, investment)
performance(my_data_eq, 8, my_data, assets[0])  

plt.plot(my_data_eq[:, 3], linewidth = 1, label = assets[0])
plt.grid()
plt.legend()
plt.axhline(y = investment, color = 'black', linewidth = 1)