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The provided code represents a trading strategy implemented as a class called "stoploss" that inherits from an interface called "IStrategy." The strategy involves backtesting various trading indicators on historical data. Here's a brief description of what the strategy does:
The method populate_indicators adds several technical analysis (TA) indicators to the given DataFrame. These indicators include ADX, RSI, Stochastic Fast, MACD, MFI, Bollinger Bands, SAR, TEMA, and Hilbert Transform Sine and Lead Sine.
The populate_buy_trend method populates the "buy" column in the DataFrame based on certain conditions.
The conditions include the RSI crossing above 30, the TEMA being below the middle Bollinger Band, the TEMA showing a rising trend, and the volume being greater than zero.
The populate_sell_trend method populates the "sell" column in the DataFrame based on certain conditions. The conditions include the RSI crossing above 70, the TEMA being above the middle Bollinger Band, the TEMA showing a falling trend, and the volume being greater than zero. Overall, this strategy combines various TA indicators to generate "buy" and "sell" signals based on the defined conditions. The strategy can be used for backtesting and evaluating the performance of different trading strategies on historical data.
The populate_buy_trend method populates the "buy" column in the DataFrame based on certain conditions.
The conditions include the RSI crossing above 30, the TEMA being below the middle Bollinger Band, the TEMA showing a rising trend, and the volume being greater than zero.
The populate_sell_trend method populates the "sell" column in the DataFrame based on certain conditions. The conditions include the RSI crossing above 70, the TEMA being above the middle Bollinger Band, the TEMA showing a falling trend, and the volume being greater than zero. Overall, this strategy combines various TA indicators to generate "buy" and "sell" signals based on the defined conditions. The strategy can be used for backtesting and evaluating the performance of different trading strategies on historical data.
startup_candle_count : 30 bb_lowerband: -0.030% bb_middleband: -0.042% bb_upperband: -0.054% bb_percent: 24.444% bb_width: -5.425% sar: -0.073%
stoploss: -0.1 timeframe: 5m hash(sha256): 3a2a57482fe4b4c7f388fa06677842a989f6f1d2d36ca69b957823b5a7fe0aa8 indicators: upper CDLDRAGONFLYDOJI CDLGRAVESTONEDOJI close CDLSPINNINGTOP bb_lowerband bb_percent CDL3WHITESOLDIERS kc_middleband volume sma10 high fisher_rsi_norma cci ha_high adx aroonosc ema50 minus_dm plus_dm CDLHANGINGMAN aroondown CDLEVENINGDOJISTAR plus_di ha_open slowk macdsignal fastk_rsi minus_di roc lower rsi sma3 sine kc_percent wbb_upperband htsine tema wbb_lowerband uo mfi ema5 kc_width macdhist CDLHAMMER htleadsine CDLEVENINGSTAR sma100 ema10 best_ask sar wbb_width CDL3OUTSIDE bids mid fisher
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last change: 2023-09-02 08:10:34