@@ -230,6 +230,7 @@ class NostalgiaForInfinityX(IStrategy):
230230 "buy_condition_48_enable" : True ,
231231 "buy_condition_49_enable" : True ,
232232 "buy_condition_50_enable" : True ,
233+ "buy_condition_51_enable" : True ,
233234 #############
234235 }
235236
@@ -1641,6 +1642,34 @@ class NostalgiaForInfinityX(IStrategy):
16411642 "close_over_pivot_offset" : 1.0 ,
16421643 "close_under_pivot_type" : "none" , # pivot, sup1, sup2, sup3, res1, res2, res3
16431644 "close_under_pivot_offset" : 1.0
1645+ },
1646+ 51 : {
1647+ "ema_fast" : False ,
1648+ "ema_fast_len" : "50" ,
1649+ "ema_slow" : False ,
1650+ "ema_slow_len" : "50" ,
1651+ "close_above_ema_fast" : False ,
1652+ "close_above_ema_fast_len" : "200" ,
1653+ "close_above_ema_slow" : False ,
1654+ "close_above_ema_slow_len" : "200" ,
1655+ "sma200_rising" : False ,
1656+ "sma200_rising_val" : "42" ,
1657+ "sma200_1h_rising" : False ,
1658+ "sma200_1h_rising_val" : "50" ,
1659+ "safe_dips_threshold_0" : 0.03 ,
1660+ "safe_dips_threshold_2" : 0.09 ,
1661+ "safe_dips_threshold_12" : None ,
1662+ "safe_dips_threshold_144" : None ,
1663+ "safe_pump_6h_threshold" : 0.5 ,
1664+ "safe_pump_12h_threshold" : 0.58 ,
1665+ "safe_pump_24h_threshold" : None ,
1666+ "safe_pump_36h_threshold" : None ,
1667+ "safe_pump_48h_threshold" : 1.1 ,
1668+ "btc_1h_not_downtrend" : False ,
1669+ "close_over_pivot_type" : "none" , # pivot, sup1, sup2, sup3, res1, res2, res3
1670+ "close_over_pivot_offset" : 1.0 ,
1671+ "close_under_pivot_type" : "none" , # pivot, sup1, sup2, sup3, res1, res2, res3
1672+ "close_under_pivot_offset" : 1.0
16441673 }
16451674 }
16461675
@@ -4748,6 +4777,7 @@ def informative_15m_indicators(self, dataframe: DataFrame, metadata: dict) -> Da
47484777
47494778 # EMAs
47504779 informative_15m ['ema_12' ] = ta .EMA (informative_15m , timeperiod = 12 )
4780+ informative_15m ['ema_16' ] = ta .EMA (informative_15m , timeperiod = 16 )
47514781 informative_15m ['ema_20' ] = ta .EMA (informative_15m , timeperiod = 20 )
47524782 informative_15m ['ema_26' ] = ta .EMA (informative_15m , timeperiod = 25 )
47534783 informative_15m ['ema_50' ] = ta .EMA (informative_15m , timeperiod = 50 )
@@ -5717,6 +5747,19 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
57175747 item_buy_logic .append (dataframe ['rsi_14' ] < 32.0 )
57185748 item_buy_logic .append (dataframe ['r_14_15m' ] < - 97.0 )
57195749
5750+ # Condition #51 - 15m. Semi swing. Downtrend. Dip.
5751+ elif index == 51 :
5752+ # Non-Standard protections
5753+
5754+ # Logic
5755+ item_buy_logic .append (dataframe ['close_15m' ] < (dataframe ['ema_16_15m' ] * 0.944 ))
5756+ item_buy_logic .append (dataframe ['ewo_15m' ] < - 1.0 )
5757+ item_buy_logic .append (dataframe ['rsi_14_15m' ] > 28.0 )
5758+ item_buy_logic .append (dataframe ['cti_15m' ] < - 0.84 )
5759+ item_buy_logic .append (dataframe ['r_14_15m' ] < - 94.0 )
5760+ item_buy_logic .append (dataframe ['rsi_14' ] > 30.0 )
5761+ item_buy_logic .append (dataframe ['crsi_1h' ] > 1.0 )
5762+
57205763 item_buy_logic .append (dataframe ['volume' ] > 0 )
57215764 item_buy = reduce (lambda x , y : x & y , item_buy_logic )
57225765 dataframe .loc [item_buy , 'buy_tag' ] += f"{ index } "
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