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The Supertrend strategy is an indicator-based trading strategy implemented for backtesting purposes on a website. The strategy utilizes the Supertrend indicator, which is adapted for use with freqtrade. The goal of the strategy is to identify potential buying and selling opportunities based on the Supertrend indicator's signals.
Here's a breakdown of what the strategy does: In the populate_indicators function: The Supertrend indicator is calculated for various combinations of multipliers and periods.
The indicator values are stored in the dataframe for each combination.
In the populate_buy_trend function: The strategy checks if the Supertrend indicator values for three different combinations of multipliers and periods are all 'up' for the current candle. It also verifies that there is some trading volume. If the conditions are met, a 'buy' signal is generated in the dataframe. In the populate_sell_trend function: The strategy checks if the Supertrend indicator values for three different combinations of multipliers and periods are all 'down' for the current candle. It also verifies that there is some trading volume. If the conditions are met, a 'sell' signal is generated in the dataframe. Additionally, the Supertrend indicator itself is calculated based on the following steps: ATR (Average True Range) and TR (True Range) are calculated for the dataframe. Upper and lower basic bounds are calculated using the high, low, and ATR values. Final upper and lower bounds are calculated based on the basic bounds and previous values. The Supertrend values are determined based on the relationship between the final bounds and previous Supertrend values. Finally, the Supertrend values are classified as 'up' or 'down' based on the close price. The strategy employs multiple combinations of multipliers and periods to capture different market conditions and generate signals accordingly.
Here's a breakdown of what the strategy does: In the populate_indicators function: The Supertrend indicator is calculated for various combinations of multipliers and periods.
The indicator values are stored in the dataframe for each combination.
In the populate_buy_trend function: The strategy checks if the Supertrend indicator values for three different combinations of multipliers and periods are all 'up' for the current candle. It also verifies that there is some trading volume. If the conditions are met, a 'buy' signal is generated in the dataframe. In the populate_sell_trend function: The strategy checks if the Supertrend indicator values for three different combinations of multipliers and periods are all 'down' for the current candle. It also verifies that there is some trading volume. If the conditions are met, a 'sell' signal is generated in the dataframe. Additionally, the Supertrend indicator itself is calculated based on the following steps: ATR (Average True Range) and TR (True Range) are calculated for the dataframe. Upper and lower basic bounds are calculated using the high, low, and ATR values. Final upper and lower bounds are calculated based on the basic bounds and previous values. The Supertrend values are determined based on the relationship between the final bounds and previous Supertrend values. Finally, the Supertrend values are classified as 'up' or 'down' based on the close price. The strategy employs multiple combinations of multipliers and periods to capture different market conditions and generate signals accordingly.
stoploss: -0.265 timeframe: 1h hash(sha256): 3c2092089970ee1bc60e8e00cba045f209d8a21e2ae3e0fac46fdb42ae0d9816 indicators: high basic_lb volume basic_ub TR supertrend_3_buy_multiplier_period ATR final_lb close STX supertrend_1_sell_multiplier_period supertrend_1_buy_multiplier_period supertrend_2_sell_multiplier_period low supertrend_3_sell_multiplier_period basic_ub basic_lb final_ub final_lb final_ub supertrend_2_buy_multiplier_period
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last change: 2022-07-02 19:54:08