@@ -4222,6 +4222,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
42224222 # Non-Standard protections (add below)
42234223
42244224 item_buy_logic = []
4225+ item_buy_logic .append (reduce (lambda x , y : x & y , buy_protection_list [34 ]))
42254226 item_buy_logic .append (dataframe ['pm' ] <= dataframe ['pmax_thresh' ])
42264227 item_buy_logic .append (dataframe ['close' ] < dataframe ['sma_75' ] * 0.98 )
42274228 item_buy_logic .append (dataframe ['ewo' ] > 8.2 )
@@ -4241,6 +4242,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
42414242 # Non-Standard protections (add below)
42424243
42434244 item_buy_logic = []
4245+ item_buy_logic .append (reduce (lambda x , y : x & y , buy_protection_list [35 ]))
42444246 item_buy_logic .append (dataframe ['pm' ] <= dataframe ['pmax_thresh' ])
42454247 item_buy_logic .append (dataframe ['close' ] < dataframe ['sma_75' ] * 0.98 )
42464248 item_buy_logic .append (dataframe ['ewo' ] < - 8.0 )
@@ -4259,6 +4261,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
42594261 # Non-Standard protections (add below)
42604262
42614263 item_buy_logic = []
4264+ item_buy_logic .append (reduce (lambda x , y : x & y , buy_protection_list [36 ]))
42624265 item_buy_logic .append (dataframe ['pm' ] > dataframe ['pmax_thresh' ])
42634266 item_buy_logic .append (dataframe ['close' ] < dataframe ['sma_75' ] * 0.93 )
42644267 item_buy_logic .append (dataframe ['ewo' ] > 8.0 )
@@ -4279,6 +4282,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
42794282 # Non-Standard protections (add below)
42804283
42814284 item_buy_logic = []
4285+ item_buy_logic .append (reduce (lambda x , y : x & y , buy_protection_list [37 ]))
42824286 item_buy_logic .append (dataframe ['pm' ] > dataframe ['pmax_thresh' ])
42834287 item_buy_logic .append (dataframe ['close' ] < dataframe ['sma_75' ] * 0.7 )
42844288 item_buy_logic .append (dataframe ['ewo' ] < - 2.0 )
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