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Trend_Triangular_MA_Distance.py
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Trend_Triangular_MA_Distance.py
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# 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 = ma(my_data, lookback, 3, 4)
my_data = ma(my_data, lookback, 4, 5)
my_data = deleter(my_data, 4, 1)
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)