The strategy described in the code is a trading strategy that uses various indicators and conditions to determine entry and exit points for trades. Here is a breakdown of what the strategy does:
The populate_indicators function is responsible for calculating and adding several indicators to the input dataframe. These indicators include moving averages (sma_15), commodity trend index (cti), relative strength index (rsi), Heikin Ashi candlestick values (ha_open, ha_close, ha_high, ha_low), Bollinger Bands (lower, mid), and others.
The strategy retrieves informative data from a different timeframe (inf_tf) using self.dp.get_pair_dataframe and merges it with the current dataframe using the merge_informative_pair function.
Additional indicators such as exponential moving averages (ema_8, ema_16, ema_12, ema_26), average directional index (adx), and stochastic fast (fastd, fastk) are calculated and added to the dataframe.
Bollinger Bands are calculated again using a different method (bollinger2) and their upper, middle, and lower bands are added to the dataframe. The width of the Bollinger Bands is also calculated. Rolling mean volumes (volume_mean_12, volume_mean_24, volume_mean_4) are calculated and added to the dataframe. The populate_entry_trend function defines the conditions for entering a trade. It checks various criteria such as the EWO (Elliott Wave Oscillator) indicator, Bollinger Bands, exponential moving averages, and closes prices to determine if a buy signal should be generated. The populate_exit_trend function is responsible for defining the conditions for exiting a trade. In the provided code, it sets the exit_long and exit_tag values to indicate that the long position should be closed. The current_profit function is used to determine the appropriate exit action based on the current profit of a trade. It checks the profit value, the "fastk" indicator, and the time elapsed since the trade was opened to decide whether to sell or continue holding the position. Overall, this strategy uses a combination of technical indicators and conditions to generate entry and exit signals for trading.
The strategy retrieves informative data from a different timeframe (inf_tf) using self.dp.get_pair_dataframe and merges it with the current dataframe using the merge_informative_pair function.
Additional indicators such as exponential moving averages (ema_8, ema_16, ema_12, ema_26), average directional index (adx), and stochastic fast (fastd, fastk) are calculated and added to the dataframe.
Bollinger Bands are calculated again using a different method (bollinger2) and their upper, middle, and lower bands are added to the dataframe. The width of the Bollinger Bands is also calculated. Rolling mean volumes (volume_mean_12, volume_mean_24, volume_mean_4) are calculated and added to the dataframe. The populate_entry_trend function defines the conditions for entering a trade. It checks various criteria such as the EWO (Elliott Wave Oscillator) indicator, Bollinger Bands, exponential moving averages, and closes prices to determine if a buy signal should be generated. The populate_exit_trend function is responsible for defining the conditions for exiting a trade. In the provided code, it sets the exit_long and exit_tag values to indicate that the long position should be closed. The current_profit function is used to determine the appropriate exit action based on the current profit of a trade. It checks the profit value, the "fastk" indicator, and the time elapsed since the trade was opened to decide whether to sell or continue holding the position. Overall, this strategy uses a combination of technical indicators and conditions to generate entry and exit signals for trading.
stoploss: -0.25 timeframe: 5m hash(sha256): 9e94c151ea91716df5994b0e0dc97886231fb8ce1780abf677fa8b3c1d35ebe0 indicators: rocr_1h upper ha_low ema_13 close tail exit_long exit_tag bb_lowerband volume_mean_12 bbdelta fastk rsi_fast bb_middleband2 volume closedelta rocr open fastd ha_open sma_15 bb_upperband2 volume_mean_24 high volume_mean_4 mid ema_8 ema_16 bb_width ha_close cti ha_high adx lower rsi_slow ema_12 bb_middleband rsi ema_slow ema_26 low bb_lowerband2
No similar strategies found. (based on used indicators)
last change: 2024-05-02 18:28:16