Buy 19: rework.

Author: iterativv

NostalgiaForInfinityNext.py

@@ -567,15 +567,15 @@ class NostalgiaForInfinityNext(IStrategy):
         },
         19: {
             "enable"                    : CategoricalParameter([True, False], default=True, space='buy', optimize=False, load=True),
-            "ema_fast"                  : CategoricalParameter([True, False], default=False, space='buy', optimize=False, load=True),
+            "ema_fast"                  : CategoricalParameter([True, False], default=True, space='buy', optimize=False, load=True),
             "ema_fast_len"              : CategoricalParameter(["26","50","100","200"], default="50", space='buy', optimize=False, load=True),
             "ema_slow"                  : CategoricalParameter([True, False], default=True, space='buy', optimize=False, load=True),
             "ema_slow_len"              : CategoricalParameter(["26","50","100","200"], default="100", space='buy', optimize=False, load=True),
             "close_above_ema_fast"      : CategoricalParameter([True, False], default=False, space='buy', optimize=False, load=True),
             "close_above_ema_fast_len"  : CategoricalParameter(["12","20","26","50","100","200"], default="200", space='buy', optimize=False, load=True),
             "close_above_ema_slow"      : CategoricalParameter([True, False], default=False, space='buy', optimize=False, load=True),
             "close_above_ema_slow_len"  : CategoricalParameter(["15","50","200"], default="200", space='buy', optimize=False, load=True),
-            "sma200_rising"             : CategoricalParameter([True, False], default=True, space='buy', optimize=False, load=True),
+            "sma200_rising"             : CategoricalParameter([True, False], default=False, space='buy', optimize=False, load=True),
             "sma200_rising_val"         : CategoricalParameter(["20","30","36","44","50"], default="36", space='buy', optimize=False, load=True),
             "sma200_1h_rising"          : CategoricalParameter([True, False], default=False, space='buy', optimize=False, load=True),
             "sma200_1h_rising_val"      : CategoricalParameter(["20","30","36","44","50"], default="50", space='buy', optimize=False, load=True),
@@ -2064,7 +2064,7 @@ class NostalgiaForInfinityNext(IStrategy):
     buy_volume_18 = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
     buy_cti_18 = DecimalParameter(-0.99, -0.5, default=-0.82, space='buy', decimals=2, optimize=False, load=True)
 
-    buy_rsi_1h_min_19 = DecimalParameter(40.0, 70.0, default=50.0, space='buy', decimals=1, optimize=False, load=True)
+    buy_rsi_1h_min_19 = DecimalParameter(40.0, 70.0, default=30.0, space='buy', decimals=1, optimize=False, load=True)
     buy_chop_min_19 = DecimalParameter(20.0, 60.0, default=23.0, space='buy', decimals=1, optimize=False, load=True)
 
     buy_rsi_20 = DecimalParameter(20.0, 36.0, default=30.0, space='buy', decimals=1, optimize=False, load=True)
@@ -3901,6 +3901,8 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
             item_buy_logic.append(dataframe['close'] > dataframe['ema_100_1h'])
             item_buy_logic.append(dataframe['rsi_1h'] > self.buy_rsi_1h_min_19.value)
             item_buy_logic.append(dataframe['chop'] < self.buy_chop_min_19.value)
+            item_buy_logic.append(dataframe['moderi_32'] == True)
+            item_buy_logic.append(dataframe['moderi_64'] == True)
             item_buy_logic.append(dataframe['moderi_96'] == True)
             item_buy_logic.append(dataframe['volume'] > 0)
             item_buy = reduce(lambda x, y: x & y, item_buy_logic)