Trend_Hull_MA_Distance.py

# Base parameters
expected_cost    = 0.0 * (lot / 100000) 
assets           = asset_list(1) 
window           = 1000

# Trading parameters   
horizon          = 'H1'

# Indicator / Strategy parameters
lookback             = 200
normalization_distance  = 20

# Mass imports 
my_data = mass_import(0, horizon)

def signal(Data, normalization_distance, buy, sell):
    
    Data = adder(Data, 2) 
    
    for i in range(len(Data)):    
        
        if Data[i, normalization_distance] == 0.0000 and Data[i - 1, buy] == 0 and \
            Data[i - 2, buy] == 0 and Data[i - 3, buy] == 0 and Data[i - 4, buy] == 0:
            Data[i, buy] = 1         
            
        elif Data[i, normalization_distance] == 100.0000 and Data[i - 1, sell] == 0 and \
            Data[i - 2, sell] == 0 and Data[i - 3, sell] == 0 and Data[i - 4, sell] == 0:
            Data[i, sell] = -1
            
    return Data

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

my_data = hull_moving_average(my_data, 3, lookback, 4)
my_data = adder(my_data, 2)
my_data[:, 5] = my_data[:, 3] - my_data[:, 4]
my_data = stochastic(my_data, normalization_period, 5, 6, genre = 'Normalization')
my_data = deleter(my_data, 5, 1)
my_data = adder(my_data, 10)
my_data = signal(my_data, 5, 6, 7)

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])

if sigchart == True:
    signal_chart_ohlc_color(my_data, assets[0], 3, 6, 7, window = 500)
    indicator_plot_double(my_data, 0, 1, 2, 3, 5, window = 500)
    plt.axhline(y = upper_barrier, color = 'black', linewidth = 1, linestyle = '--')
    plt.axhline(y = lower_barrier, color = 'black', linewidth = 1, linestyle = '--')    

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