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The NFI46Frog strategy is a trading strategy implemented as a class that inherits from the IStrategy class. Here's a brief description of what the strategy does:
The populate_indicators method is responsible for populating the indicators used in the strategy. It takes a DataFrame and metadata as input and returns a modified DataFrame with additional indicator columns.
The method first calculates indicators for a 1-hour timeframe (informative_1h) using the informative_1h_indicators function.
It then stores trade information specific to the trading pair in the custom_trade_info dictionary.
Next, it checks the runmode configuration parameter to determine the timeframe for further calculations. If the timeframe is the same as the 1-hour timeframe (inf_1h), the indicators are calculated directly using the do_indicators function. Otherwise, it retrieves additional informative data for the trading pair and calculates the indicators using the do_indicators function. Finally, it merges the informative data with the original DataFrame and performs some column renaming and further calculations if the runmode is in backtest or hyperopt. The populate_buy_trend method is responsible for populating the buy trend of the strategy. It takes a DataFrame and metadata as input and returns a modified DataFrame with additional buy trend columns. The method defines multiple conditions for triggering a buy signal based on various indicators and configurations. Each condition is appended to a list of conditions. The conditions involve comparisons and calculations using indicators such as moving averages (ema_50_1h, ema_200_1h, sma_200), safe dips and pumps, relative strength index (rsi_1h, rsi), money flow index (mfi), Bollinger Bands (bb_lowerband), volume, and more. The conditions are combined using logical operators. If any of the conditions are met, a buy signal is generated for the corresponding timeframe. Overall, the NFI46Frog strategy combines multiple indicators and conditions to generate buy signals for different trading scenarios and timeframes.
The method first calculates indicators for a 1-hour timeframe (informative_1h) using the informative_1h_indicators function.
It then stores trade information specific to the trading pair in the custom_trade_info dictionary.
Next, it checks the runmode configuration parameter to determine the timeframe for further calculations. If the timeframe is the same as the 1-hour timeframe (inf_1h), the indicators are calculated directly using the do_indicators function. Otherwise, it retrieves additional informative data for the trading pair and calculates the indicators using the do_indicators function. Finally, it merges the informative data with the original DataFrame and performs some column renaming and further calculations if the runmode is in backtest or hyperopt. The populate_buy_trend method is responsible for populating the buy trend of the strategy. It takes a DataFrame and metadata as input and returns a modified DataFrame with additional buy trend columns. The method defines multiple conditions for triggering a buy signal based on various indicators and configurations. Each condition is appended to a list of conditions. The conditions involve comparisons and calculations using indicators such as moving averages (ema_50_1h, ema_200_1h, sma_200), safe dips and pumps, relative strength index (rsi_1h, rsi), money flow index (mfi), Bollinger Bands (bb_lowerband), volume, and more. The conditions are combined using logical operators. If any of the conditions are met, a buy signal is generated for the corresponding timeframe. Overall, the NFI46Frog strategy combines multiple indicators and conditions to generate buy signals for different trading scenarios and timeframes.
startup_candle_count : 400 ema_200_1h: 0.035% ema_200: -0.013% ewo: 1.969%
stoploss: -1 timeframe: 5m hash(sha256): bdad559e841db312e5470d0d399fe6552c13864922ce1eff3c147be592393a33 indicators: sell_pump_36_3_1h sma_200_1h upper close HA_Close ema_15 sell_pump_36_2 safe_pump_36_strict sell_pump_24_1_1h bb_lowerband sma_5 ema_200_1h ewo date candleuptrend safe_pump_24 HA_High volume smaHigh sslDown sell_pump_36_1_1h ema_20 safe_pump_48_1h safe_pump_24_1h DI sell_pump_48_1_1h bb_upperband_1h safe_pump_36_1h high sslUp emac date sroc safe_pump_24_normal sell_pump_48_3 rsi_1h atr adx openclosehigh hhlow ema_12 sell_pump_48_2 ema_26 runmode safe_pump_24_strict_1h Smooth_HA_C active_trade HA
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last change: 2024-05-02 21:02:24