The MontrealStrategy class is a trading strategy implementation that uses technical analysis (TA) indicators to generate buy and sell signals for a given DataFrame of market data. Here's a breakdown of what the strategy does:
populate_indicators function:
Calculates the Relative Strength Index (RSI) indicator and adds it as a column named "rsi" to the DataFrame. Calculates Bollinger Bands with a standard deviation of 1, 2, and 4, and adds the lower, middle, and upper bands as columns to the DataFrame.
populate_buy_trend function: Uses the TA indicators to determine the buy signal conditions.
If the RSI is greater than 30, the close price is below the 2-standard deviation Bollinger Bands lower band, and the volume is greater than 0, it sets the "buy" column in the DataFrame to 1 for those corresponding rows.
populate_sell_trend function: Uses the TA indicators to determine the sell signal conditions. If the close price is above the 2-standard deviation Bollinger Bands upper band and the volume is greater than 0, it sets the "sell" column in the DataFrame to 1 for those corresponding rows. The strategy's purpose is to provide signals for buying and selling based on the calculated indicators. By backtesting this strategy on historical data, you can evaluate its performance and potentially make informed trading decisions.
populate_buy_trend function: Uses the TA indicators to determine the buy signal conditions.
If the RSI is greater than 30, the close price is below the 2-standard deviation Bollinger Bands lower band, and the volume is greater than 0, it sets the "buy" column in the DataFrame to 1 for those corresponding rows.
populate_sell_trend function: Uses the TA indicators to determine the sell signal conditions. If the close price is above the 2-standard deviation Bollinger Bands upper band and the volume is greater than 0, it sets the "sell" column in the DataFrame to 1 for those corresponding rows. The strategy's purpose is to provide signals for buying and selling based on the calculated indicators. By backtesting this strategy on historical data, you can evaluate its performance and potentially make informed trading decisions.
stoploss: -0.286 timeframe: 5m hash(sha256): 00d7b1be6b3ace916f876a375e07351c896005ef276e21936a83e27a94a7e009 indicators: bb4_middleband bb1_middleband volume bb4_upperband close rsi bb2_middleband bb2_upperband bb4_lowerband bb1_upperband bb1_lowerband bb2_lowerband
No similar strategies found. (based on used indicators)
last change: 2024-05-02 07:59:42