From 81530c1dbbf5d4c8cb5572f59352d654ec7e0d63 Mon Sep 17 00:00:00 2001 From: iterativ Date: Thu, 11 Nov 2021 20:25:59 +0200 Subject: [PATCH] Buy 51: 15m. Semi swing. Deep local dip. Mild 15m uptrend. --- NostalgiaForInfinityX.py | 43 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 43 insertions(+) diff --git a/NostalgiaForInfinityX.py b/NostalgiaForInfinityX.py index 1e89260015..867f5961a5 100644 --- a/NostalgiaForInfinityX.py +++ b/NostalgiaForInfinityX.py @@ -230,6 +230,7 @@ class NostalgiaForInfinityX(IStrategy): "buy_condition_48_enable": True, "buy_condition_49_enable": True, "buy_condition_50_enable": True, + "buy_condition_51_enable": True, ############# } @@ -1641,6 +1642,34 @@ class NostalgiaForInfinityX(IStrategy): "close_over_pivot_offset" : 1.0, "close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3 "close_under_pivot_offset" : 1.0 + }, + 51: { + "ema_fast" : False, + "ema_fast_len" : "50", + "ema_slow" : False, + "ema_slow_len" : "50", + "close_above_ema_fast" : False, + "close_above_ema_fast_len" : "200", + "close_above_ema_slow" : False, + "close_above_ema_slow_len" : "200", + "sma200_rising" : False, + "sma200_rising_val" : "42", + "sma200_1h_rising" : False, + "sma200_1h_rising_val" : "50", + "safe_dips_threshold_0" : 0.03, + "safe_dips_threshold_2" : 0.09, + "safe_dips_threshold_12" : None, + "safe_dips_threshold_144" : None, + "safe_pump_6h_threshold" : 0.5, + "safe_pump_12h_threshold" : 0.58, + "safe_pump_24h_threshold" : None, + "safe_pump_36h_threshold" : None, + "safe_pump_48h_threshold" : 1.1, + "btc_1h_not_downtrend" : False, + "close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3 + "close_over_pivot_offset" : 1.0, + "close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3 + "close_under_pivot_offset" : 1.0 } } @@ -4748,6 +4777,7 @@ def informative_15m_indicators(self, dataframe: DataFrame, metadata: dict) -> Da # EMAs informative_15m['ema_12'] = ta.EMA(informative_15m, timeperiod=12) + informative_15m['ema_16'] = ta.EMA(informative_15m, timeperiod=16) informative_15m['ema_20'] = ta.EMA(informative_15m, timeperiod=20) informative_15m['ema_26'] = ta.EMA(informative_15m, timeperiod=25) informative_15m['ema_50'] = ta.EMA(informative_15m, timeperiod=50) @@ -5717,6 +5747,19 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: item_buy_logic.append(dataframe['rsi_14'] < 32.0) item_buy_logic.append(dataframe['r_14_15m'] < -97.0) + # Condition #51 - 15m. Semi swing. Downtrend. Dip. + elif index == 51: + # Non-Standard protections + + # Logic + item_buy_logic.append(dataframe['close_15m'] < (dataframe['ema_16_15m'] * 0.944)) + item_buy_logic.append(dataframe['ewo_15m'] < -1.0) + item_buy_logic.append(dataframe['rsi_14_15m'] > 28.0) + item_buy_logic.append(dataframe['cti_15m'] < -0.84) + item_buy_logic.append(dataframe['r_14_15m'] < -94.0) + item_buy_logic.append(dataframe['rsi_14'] > 30.0) + item_buy_logic.append(dataframe['crsi_1h'] > 1.0) + item_buy_logic.append(dataframe['volume'] > 0) item_buy = reduce(lambda x, y: x & y, item_buy_logic) dataframe.loc[item_buy, 'buy_tag'] += f"{index} "