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The "x_strat" trading strategy is designed to be used for backtesting on a trading platform. Here is a description of what the strategy does:
The strategy uses various technical indicators to make trading decisions. It imports the "talib" library for calculating technical indicators and the "qtpylib" library for additional indicator functions.
The strategy has a predefined stop loss of -0.2, which means that if a trade's price drops by 0.2 units from the entry price, the trade will be closed with a market order.
The timeframe for the strategy is set to "1d", indicating that it operates on daily candlestick data.
The order types for buying and selling are set to "limit" orders, meaning that the strategy will place orders at a specific price. The strategy defines a minimum RSI (Relative Strength Index) lower threshold of 25 for triggering buy signals. The strategy calculates additional indicators such as MFI (Money Flow Index), SMA (Simple Moving Average), and Bollinger Bands. Bollinger Bands consist of three lines: the upper band, middle band, and lower band. The strategy calculates the percentage of the close price relative to the Bollinger Bands to identify potential trading opportunities. The "populate_indicators" function is used to populate the indicator values in the dataframe. The "populate_buy_trend" function determines when to generate buy signals based on specific conditions. In the current implementation, the buy signal is triggered when the RSI is below the predefined lower threshold. The "populate_sell_trend" function generates sell signals without any specific conditions, indicating that the strategy will sell without considering any additional factors. Note: The strategy includes commented-out sections that are not active in the current implementation.
The strategy has a predefined stop loss of -0.2, which means that if a trade's price drops by 0.2 units from the entry price, the trade will be closed with a market order.
The timeframe for the strategy is set to "1d", indicating that it operates on daily candlestick data.
The order types for buying and selling are set to "limit" orders, meaning that the strategy will place orders at a specific price. The strategy defines a minimum RSI (Relative Strength Index) lower threshold of 25 for triggering buy signals. The strategy calculates additional indicators such as MFI (Money Flow Index), SMA (Simple Moving Average), and Bollinger Bands. Bollinger Bands consist of three lines: the upper band, middle band, and lower band. The strategy calculates the percentage of the close price relative to the Bollinger Bands to identify potential trading opportunities. The "populate_indicators" function is used to populate the indicator values in the dataframe. The "populate_buy_trend" function determines when to generate buy signals based on specific conditions. In the current implementation, the buy signal is triggered when the RSI is below the predefined lower threshold. The "populate_sell_trend" function generates sell signals without any specific conditions, indicating that the strategy will sell without considering any additional factors. Note: The strategy includes commented-out sections that are not active in the current implementation.
startup_candle_count : 50 rsi: 0.269%
stoploss: -0.2 timeframe: 5m hash(sha256): e4626061a3e60188c98c96c050e755bedb7da0d45ab6e4b6e18427db5d095e5b indicators: lowerband bb_lower close rsi mfi bb_upper bb_percent middleband bb_middle sma upperband
No similar strategies found. (based on used indicators)
last change: 2023-08-03 19:14:37