The strategy, named CombinedBinHAndClucV8XHO, is a trading strategy implemented as a class that inherits from the IStrategy interface. Here is a breakdown of what the strategy does:
populate_indicators: This function is responsible for populating the indicators used in the strategy. It takes a DataFrame and metadata as input and returns the modified DataFrame after adding the indicators.
populate_buy_trend: This function determines the conditions for buying based on various indicators and thresholds.
It defines a list of conditions that need to be met for a buy signal.
Some of the important conditions include: The closing price is above the 200-period exponential moving average (ema) on the current timeframe and the 1-hour timeframe. The 50-period ema is above the 200-period ema on both the current and 1-hour timeframes. The open price dip thresholds are met. The lower Bollinger Band is positive, and other Bollinger Band and tail conditions are met. The volume is greater than zero. If any of the conditions are met, a 'buy' signal is generated for the corresponding row in the DataFrame. populate_sell_trend: This function determines the conditions for selling based on various indicators and thresholds. It defines a list of conditions that need to be met for a sell signal. Some of the important conditions include: The closing price is above the upper Bollinger Band for the current and previous three periods. The RSI (Relative Strength Index) is above a specified threshold. The volume is greater than zero. If any of the conditions are met, a 'sell' signal is generated for the corresponding row in the DataFrame. The strategy combines multiple technical indicators and conditions to generate buy and sell signals for trading. It uses moving averages, Bollinger Bands, open price dips, RSI, and volume to make trading decisions.
populate_buy_trend: This function determines the conditions for buying based on various indicators and thresholds.
It defines a list of conditions that need to be met for a buy signal.
Some of the important conditions include: The closing price is above the 200-period exponential moving average (ema) on the current timeframe and the 1-hour timeframe. The 50-period ema is above the 200-period ema on both the current and 1-hour timeframes. The open price dip thresholds are met. The lower Bollinger Band is positive, and other Bollinger Band and tail conditions are met. The volume is greater than zero. If any of the conditions are met, a 'buy' signal is generated for the corresponding row in the DataFrame. populate_sell_trend: This function determines the conditions for selling based on various indicators and thresholds. It defines a list of conditions that need to be met for a sell signal. Some of the important conditions include: The closing price is above the upper Bollinger Band for the current and previous three periods. The RSI (Relative Strength Index) is above a specified threshold. The volume is greater than zero. If any of the conditions are met, a 'sell' signal is generated for the corresponding row in the DataFrame. The strategy combines multiple technical indicators and conditions to generate buy and sell signals for trading. It uses moving averages, Bollinger Bands, open price dips, RSI, and volume to make trading decisions.
startup_candle_count : 200 ema_50_1h: 0.001% ema_100_1h: -0.041%
stoploss: -0.99 timeframe: 5m hash(sha256): b8c89de71394d980a336d6e26ff067365e5d084add2c91f936c38dcf5304af64 indicators: sma_200_1h upper ema_200 ema_50 close sma_5 tail bb_lowerband mfi ema_200_1h bbdelta volume smaHigh ATR ema_100_1h ssl_up closedelta sslDown open hlv volume_mean_slow ema_50_1h smaLow sma_200 high sslUp mid ssl_down_1h ssl_down rsi_1h ema_100 lower ema_12 bb_middleband rsi sma_200_dec bb_upperband ema_slow ema_26 low ssl_up_1h sma_200_dec_1h
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last change: 2024-05-02 20:40:48