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Bottle.py

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+
+# 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)
+
+def signal(Data):
+    for i in range(len(Data)):        
+       # Bullish Bottle
+       if Data[i, 3] > Data[i, 0] and Data[i, 0] == Data[i, 2]: 
+                Data[i, 6] = 1 
+       # Bearish Bottle
+       if Data[i, 3] < Data[i, 0] and Data[i, 0] == Data[i, 1]: 
+                Data[i, 7] = -1
+
+
+##############################################################################   1
+
+my_data = adder(my_data, 10)
+my_data = rounding(my_data, 4)
+signal(my_data)
+
+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)

Contrarian_Countdown_Duration.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         =   8
+ma_lookback      =   3
+cross_ma_lookback = 13
+upper_barrier    =  5
+lower_barrier    = -5
+
+# Mass imports 
+my_data = mass_import(0, horizon)
+
+def signal(Data, extreme, buy, sell):
+
+    Data = adder(Data, 10)
+
+    for i in range(len(Data)):
+
+        if Data[i, extreme] <= -5 and Data[i - 1, buy] == 0 and Data[i - 2, buy] == 0 and Data[i - 3, buy] == 0:
+            Data[i, buy] = 1
+
+        elif Data[i, extreme] >= 5 and Data[i - 1, sell] == 0 and Data[i - 2, sell] == 0 and Data[i - 3, sell] == 0:
+            Data[i, sell] = -1   
+
+    return Data    
+
+##############################################################################   1
+
+my_data = countdown_indicator(my_data, lookback, ma_lookback, 0, 1, 2, 3, 4)
+my_data = extreme_duration(my_data, 4, upper_barrier, lower_barrier, 7, 6, 8)
+my_data = deleter(my_data, 5, 1)
+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 = 250)
+    plt.axhline(y = 5, color = 'black', linewidth = 1, linestyle = '--')
+    plt.axhline(y = -5, 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)

Contrarian_Demarker_Duration.py

@@ -0,0 +1,52 @@
+
+# Base parameters
+expected_cost    = 0.0 * (lot / 100000) 
+assets           = asset_list(1) 
+window           = 1000
+
+# Trading parameters   
+horizon          = 'H1'
+
+# Indicator / Strategy parameters
+lookback         =   14
+upper_barrier    =  0.7
+lower_barrier    =  0.3
+
+# Mass imports 
+my_data = mass_import(0, horizon)
+
+def signal(Data, extreme, buy, sell):
+
+    Data = adder(Data, 10)
+
+    for i in range(len(Data)):
+
+        if Data[i, extreme] <= -5 and Data[i - 1, buy] == 0 and Data[i - 2, buy] == 0 and Data[i - 3, buy] == 0:
+            Data[i, buy] = 1
+
+        elif Data[i, extreme] >= 5 and Data[i - 1, sell] == 0 and Data[i - 2, sell] == 0 and Data[i - 3, sell] == 0:
+            Data[i, sell] = -1   
+
+    return Data    
+
+##############################################################################   1
+
+my_data = demarker(my_data, lookback, 1, 2, 4)
+my_data = extreme_duration(my_data, 4, upper_barrier, lower_barrier, 7, 6, 8)
+my_data = deleter(my_data, 5, 1)
+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 = 250)
+    plt.axhline(y = 5, color = 'black', linewidth = 1, linestyle = '--')
+    plt.axhline(y = -5, 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)

Contrarian_Disparity_Index_Extremes.py

@@ -0,0 +1,53 @@
+
+# Base parameters
+expected_cost    = 0.0 * (lot / 100000) 
+assets           = asset_list(1) 
+window           = 1000
+
+# Trading parameters   
+horizon          = 'H1'
+
+# Indicator / Strategy parameters
+lookback         = 14
+upper_barrier    = 0.2
+lower_barrier    = -0.2
+
+# Mass imports 
+my_data = mass_import(0, horizon)
+
+def signal(Data, what, buy, sell):
+
+    Data = adder(Data, 10)
+    Data = rounding(Data, 5)
+
+    for i in range(len(Data)):
+
+        if Data[i, what] <= lower_barrier 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, what] >= upper_barrier 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 = disparity_index(my_data, lookback, 3, 4)
+my_data = signal(my_data, 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)
+    indicator_plot_double(my_data, 0, 1, 2, 3, 4, window = 250)
+    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)

Contrarian_Fisher_Duration.py

@@ -0,0 +1,52 @@
+
+# Base parameters
+expected_cost    = 0.0 * (lot / 100000) 
+assets           = asset_list(1) 
+window           = 1000
+
+# Trading parameters   
+horizon          = 'H1'
+
+# Indicator / Strategy parameters
+lookback         =   14
+upper_barrier    =  1.0
+lower_barrier    = -1.0
+
+# Mass imports 
+my_data = mass_import(0, horizon)
+
+def signal(Data, extreme, buy, sell):
+
+    Data = adder(Data, 10)
+
+    for i in range(len(Data)):
+
+        if Data[i, extreme] <= -5 and Data[i - 1, buy] == 0 and Data[i - 2, buy] == 0 and Data[i - 3, buy] == 0:
+            Data[i, buy] = 1
+
+        elif Data[i, extreme] >= 5 and Data[i - 1, sell] == 0 and Data[i - 2, sell] == 0 and Data[i - 3, sell] == 0:
+            Data[i, sell] = -1   
+
+    return Data    
+
+##############################################################################   1
+
+my_data = fisher_transform(my_data, lookback, 3, 4)
+my_data = extreme_duration(my_data, 4, upper_barrier, lower_barrier, 7, 6, 8)
+my_data = deleter(my_data, 5, 1)
+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 = 250)
+    plt.axhline(y = 5, color = 'black', linewidth = 1, linestyle = '--')
+    plt.axhline(y = -5, 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)

Contrarian_RSI_Duration.py

@@ -0,0 +1,52 @@
+
+# Base parameters
+expected_cost    = 0.0 * (lot / 100000) 
+assets           = asset_list(1) 
+window           = 1000
+
+# Trading parameters   
+horizon          = 'H1'
+
+# Indicator / Strategy parameters
+lookback         =   14
+upper_barrier    =  70
+lower_barrier    =  30
+
+# Mass imports 
+my_data = mass_import(0, horizon)
+
+def signal(Data, extreme, buy, sell):
+
+    Data = adder(Data, 10)
+
+    for i in range(len(Data)):
+
+        if Data[i, extreme] <= -5 and Data[i - 1, buy] == 0 and Data[i - 2, buy] == 0 and Data[i - 3, buy] == 0:
+            Data[i, buy] = 1
+
+        elif Data[i, extreme] >= 5 and Data[i - 1, sell] == 0 and Data[i - 2, sell] == 0 and Data[i - 3, sell] == 0:
+            Data[i, sell] = -1   
+
+    return Data    
+
+##############################################################################   1
+
+my_data = rsi(my_data, lookback, 3, 4, genre = 'Smoothed')
+my_data = extreme_duration(my_data, 4, upper_barrier, lower_barrier, 7, 6, 8)
+my_data = deleter(my_data, 5, 1)
+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 = 250)
+    plt.axhline(y = 5, color = 'black', linewidth = 1, linestyle = '--')
+    plt.axhline(y = -5, 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)

Contrarian_Real_Range_Extremes.py

@@ -0,0 +1,53 @@
+
+# Base parameters
+expected_cost    = 0.0 * (lot / 100000) 
+assets           = asset_list(1) 
+window           = 1000
+
+# Trading parameters   
+horizon          = 'H1'
+
+# Indicator / Strategy parameters
+lookback         = 1
+upper_barrier    =  2
+lower_barrier    = -2
+
+# Mass imports 
+my_data = mass_import(0, horizon)
+
+def signal(Data, what, buy, sell):
+
+    Data = adder(Data, 10)
+    Data = rounding(Data, 5)
+
+    for i in range(len(Data)):
+
+        if Data[i, what] <= lower_barrier 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, what] >= upper_barrier 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 = rri(my_data, lookback, 4)
+my_data = signal(my_data, 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)
+    indicator_plot_double(my_data, 0, 1, 2, 3, 4, window = 250)
+    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)