Strategy: BigPeteBU
Downloaded: 20220224
Stoploss: -0.99

Not Enough Data to display!

Average Overall
Not Enough Data! / Avg statistics not populated yet.
The BigPete strategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It involves populating indicators and defining conditions for buying trends. Here's a breakdown of its main components: populate_indicators method: Retrieves informative 1-hour indicators and merges them with the current timeframe indicators.

Returns the updated dataframe.

populate_buy_trend method: Defines multiple buy conditions using a list named conditions.

Each condition is a combination of various criteria expressed as logical expressions. These conditions specify when to enter a buy trade based on indicators such as moving averages (ema), Bollinger Bands (bb), relative strength index (rsi), historical data (hist), and volume. Each condition is appended to the conditions list. The strategy aims to identify specific patterns or signals in the market to generate buy signals. It considers indicators like moving averages, Bollinger Bands, RSI, historical data, and volume to determine the timing of entry into a trade. Please note that the provided code snippet may not be complete, and additional methods or logic may exist within the BigPete class or the IStrategy interface.

stoploss: -0.99
timeframe: 5m
hash(sha256): 0d907f89fab62011eaebcb70acbcbde0dad6c0d390e85c43dd9e67eeb0542bd5
buy_rsi_1h_2 buy_rsi_1h_4 buy_rsi_1h_1a upper buy_volume_drop_2
ema_200 ema_50 narrow_stop close buy_condition_4_enable
buy_condition_9_enable buy_rsi_0 sma_5 bb_lowerband buy_rsi_1h_5
rsi_1h_val ema_200_1h buy_volume_drop_1 ma_sell_val buy_condition_6_enable
buy_rsi_1h_0 pPF_2 buy_rsi_1 buy_condition_0_enable buy_condition_1_enable
pSL_1 pSL_2 buy_condition_3_enable volume buy_macd_2
high_offset buy_bb20_close_bblowerband_safe_2 open buy_volume_drop_3 volume_mean_slow
buy_condition_7_enable pHS

Similar Strategies: (based on used indicators)

Strategy: BigPete, Similarity Score: 97.37%

last change: 2023-06-30 12:43:18