Strategy: f_supertrend_strategy_2
Downloaded: 20220531
Stoploss: -0.2

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The FSupertrendStrategy is a trading strategy implemented for backtesting purposes on a website. It uses the Supertrend indicator to generate buy and sell signals based on certain conditions. Here's a breakdown of what the strategy does: In the populate_indicators method, the Supertrend indicator is calculated for different combinations of multipliers and periods.

The indicator values are added as columns to the input dataframe.

In the populate_entry_trend method, the strategy identifies potential entry points for long and short positions.

It checks if specific Supertrend indicators meet certain criteria (e.g., "up" for the current candle) and if the volume is greater than zero. If the conditions are met, the corresponding columns (enter_long and enter_short) in the dataframe are set to 1. In the populate_exit_trend method, the strategy identifies potential exit points for long and short positions. It checks if a specific Supertrend indicator meets certain criteria (e.g., "down" for the current candle). If the condition is met, the corresponding exit columns (exit_long and exit_short) in the dataframe are set to 1. The Supertrend indicator calculation is performed in the commented code section. It calculates the Supertrend values (ST and STX) based on the period, multiplier, and price data in the input dataframe. The calculated values are returned as a new DataFrame. Overall, the FSupertrendStrategy applies the Supertrend indicator to identify potential entry and exit points for trading positions based on user-defined parameters.

stoploss: -0.2
timeframe: 5m
hash(sha256): c4dd15642bc786c75140a05f92fde3d4d69b3b6fb12926d94f9e8a0cd91f457a
f"supertrend_2_buy_multiplier_period volume f"supertrend_1_buy_multiplier_period f"supertrend_3_sell_multiplier_period f"supertrend_1_sell_multiplier_period
f"supertrend_3_buy_multiplier_period f"supertrend_2_sell_multiplier_period

No similar strategies found. (based on used indicators)

last change: 2023-10-26 12:02:38