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The Supertrend strategy is a popular technical analysis indicator adapted for backtesting in trading. The strategy aims to identify potential buy and sell signals based on the Supertrend indicator. Here's a breakdown of how the strategy works:
In the populate_indicators function, the Supertrend indicator is calculated for different combinations of multiplier and period values.
Multiple Supertrend indicators are created for both buy and sell signals.
The populate_buy_trend function populates a "buy" signal in the dataframe when certain conditions are met: The three Supertrend indicators for buying are in an "up" state.
The closing price two candles ago is lower than the 200-period Exponential Moving Average (ema200). There is some trading volume. The populate_sell_trend function populates a "sell" signal in the dataframe when certain conditions are met: The three Supertrend indicators for selling are in a "down" state. There is some trading volume. The Supertrend indicator calculation involves several steps: Calculate the True Range (TR) and Average True Range (ATR) for the given dataframe. Calculate upper and lower bands (basic_ub and basic_lb) based on the high, low, and ATR values. Calculate final upper and lower bands (final_ub and final_lb) by comparing with previous values and the closing price. Determine the Supertrend values (st) based on the final_ub and final_lb values. Determine the Supertrend trend states (stx) as "up" or "down" based on the Supertrend values and the closing price. Finally, unnecessary columns are dropped, NaN values are filled with zeros, and a new dataframe is returned with the Supertrend values (ST) and trend states (STX). Overall, the Supertrend strategy aims to generate buy signals when the Supertrend indicators align in an upward direction and certain additional conditions are met, and sell signals when the Supertrend indicators align in a downward direction and other conditions are satisfied.
Multiple Supertrend indicators are created for both buy and sell signals.
The populate_buy_trend function populates a "buy" signal in the dataframe when certain conditions are met: The three Supertrend indicators for buying are in an "up" state.
The closing price two candles ago is lower than the 200-period Exponential Moving Average (ema200). There is some trading volume. The populate_sell_trend function populates a "sell" signal in the dataframe when certain conditions are met: The three Supertrend indicators for selling are in a "down" state. There is some trading volume. The Supertrend indicator calculation involves several steps: Calculate the True Range (TR) and Average True Range (ATR) for the given dataframe. Calculate upper and lower bands (basic_ub and basic_lb) based on the high, low, and ATR values. Calculate final upper and lower bands (final_ub and final_lb) by comparing with previous values and the closing price. Determine the Supertrend values (st) based on the final_ub and final_lb values. Determine the Supertrend trend states (stx) as "up" or "down" based on the Supertrend values and the closing price. Finally, unnecessary columns are dropped, NaN values are filled with zeros, and a new dataframe is returned with the Supertrend values (ST) and trend states (STX). Overall, the Supertrend strategy aims to generate buy signals when the Supertrend indicators align in an upward direction and certain additional conditions are met, and sell signals when the Supertrend indicators align in a downward direction and other conditions are satisfied.
stoploss: -0.99 timeframe: 1h hash(sha256): 898fdd2fa520e9de434bef48cd4ad1a9894909577fe8473cc719a58aaad9c318 indicators: basic_ub close supertrend_3_sell_multiplier_period volume ATR STX supertrend_1_sell_multiplier_period supertrend_2_buy_multiplier_period high supertrend_3_buy_multiplier_period supertrend_2_sell_multiplier_period final_ub ema200 basic_lb TR final_lb supertrend_1_buy_multiplier_period low basic_ub basic_lb final_ub final_lb
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last change: 2023-02-08 11:45:42