Trend_MA_Cross.py

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

# Trading parameters   
horizon          = 'H1'

# Indicator / Strategy parameters
lookback         =   200

# Mass imports 
my_data = mass_import(0, horizon)

def signal(Data, close, ma_column, buy_col, sell_col):
    
    Data = adder(Data, 10)
    for i in range(len(Data)):
        
        # Scanning for Bullish signals
        if Data[i, close] > Data[i, ma_column] and Data[i - 1, close] < Data[i - 1, ma_column]:
            Data[i, buy_col] = 1
            
        # Scanning for Bearish signals
        elif Data[i, close] < Data[i, ma_column] and Data[i - 1, close] > Data[i - 1, ma_column]:
            Data[i, sell_col] = -1
            
    return Data


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

my_data = ma(my_data, lookback, 3, 4)
my_data = signal(my_data, 3, 4, 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)
    plt.plot(my_data[-500:, 4])
    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)