The SARCross strategy is a trading strategy that uses various technical indicators to generate buy and sell signals. Here is a breakdown of what the strategy does:
populate_indicators method:
Adds several technical indicators to the given DataFrame, including ADX, PLUS_DM, PLUS_DI, MINUS_DM, MINUS_DI, RSI, Fisher RSI, Stochastic Fast, MACD, MFI, Bollinger Bands, EMA, SAR, and TEMA. These indicators provide information about trend strength, directional movement, momentum, volume, and volatility.
populate_entry_trend method: Based on the populated indicators, determines the buy signal for the DataFrame.
The strategy considers conditions such as ADX value, delta of directional movement, MFI value, Fisher RSI value, volume, and Bollinger Bands gain.
If all the conditions are met, the 'buy' column in the DataFrame is set to 1. populate_exit_trend method: Based on the populated indicators, determines the sell signal for the DataFrame. The strategy considers conditions such as SAR crossing above TEMA. If the condition is met, the 'sell' column in the DataFrame is set to 1. Overall, the SARCross strategy combines multiple indicators to identify potential buying opportunities (based on entry conditions) and selling opportunities (based on exit conditions) in the market.
populate_entry_trend method: Based on the populated indicators, determines the buy signal for the DataFrame.
The strategy considers conditions such as ADX value, delta of directional movement, MFI value, Fisher RSI value, volume, and Bollinger Bands gain.
If all the conditions are met, the 'buy' column in the DataFrame is set to 1. populate_exit_trend method: Based on the populated indicators, determines the sell signal for the DataFrame. The strategy considers conditions such as SAR crossing above TEMA. If the condition is met, the 'sell' column in the DataFrame is set to 1. Overall, the SARCross strategy combines multiple indicators to identify potential buying opportunities (based on entry conditions) and selling opportunities (based on exit conditions) in the market.
stoploss: 0 timeframe: 5m hash(sha256): 59aff40c37fe77874f9e83708bc24eebc71ccaf65406826ea9be245861910da8 indicators: upper tema close dm_delta bb_gain mfi bb_lowerband bb_percent fastk macdhist volume fastd dm_plus sar macdsignal mid fisher_rsi bb_width di_plus fisher_rsi_norma macd di_delta ema7 ema25 adx lower bb_middleband rsi di_minus bb_upperband dm_minus
Similar Strategies: (based on used indicators)
Strategy: BTCMACDCross, Similarity Score: 96.88%
Strategy: BTCMACDCross_2, Similarity Score: 96.88%
Strategy: MACDCross_2, Similarity Score: 96.88%
Strategy: SARCross, Similarity Score: 96.88%
Strategy: MACDTurn, Similarity Score: 93.75%
Strategy: MACDTurn_2, Similarity Score: 93.75%
last change: 2024-04-28 23:52:22