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The "slope_is_dopeCT" strategy is a backtesting strategy that uses various indicators to generate buy and sell signals. Here is a short description of what the strategy does:
In the "populate_indicators" function:
Calculates the Relative Strength Index (RSI) with a time period of 7. Computes moving averages: marketMA (200 periods), fastMA (21 periods), slowMA (50 periods), entryMA (3 periods).
Shifts the slowMA values based on the slope length.
Calculates the difference between two shifted slowMA values and assigns it to "sy." Computes the slope of the slowMA by dividing "sy" by the difference in x-values.
Shifts the fastMA values based on the slope length. Calculates the difference between two shifted fastMA values and assigns it to "fy." Computes the slope of the fastMA by dividing "fy" by the difference in x-values. Calculates the lowest value of "low" over a specified stoploss length and assigns it to "last_lowest." Returns the updated dataframe. The "plot_config" dictionary specifies the configurations for plotting the main plot (fastMA and slowMA) and subplots (rsi, fast_slope, and slow_slope). In the "populate_buy_trend" function: Identifies buy opportunities based on the following conditions: Fast slope is greater than a specified value (fslope_buy). Slow slope is greater than a specified value (sslope_buy). Current close price is higher than the close price shifted by the slope length. RSI is greater than a specified value (rsi_buy). Sets the "buy" column to 1 for the corresponding buy signals. In the "populate_sell_trend" function: Identifies sell opportunities based on the following conditions: Fast slope is less than a specified value (fslope_sell). Current close price is lower than the last lowest price. Sets the "sell" column to 1 for the corresponding sell signals. The strategy uses these buy and sell signals to evaluate the performance of the trading strategy during backtesting.
Shifts the slowMA values based on the slope length.
Calculates the difference between two shifted slowMA values and assigns it to "sy." Computes the slope of the slowMA by dividing "sy" by the difference in x-values.
Shifts the fastMA values based on the slope length. Calculates the difference between two shifted fastMA values and assigns it to "fy." Computes the slope of the fastMA by dividing "fy" by the difference in x-values. Calculates the lowest value of "low" over a specified stoploss length and assigns it to "last_lowest." Returns the updated dataframe. The "plot_config" dictionary specifies the configurations for plotting the main plot (fastMA and slowMA) and subplots (rsi, fast_slope, and slow_slope). In the "populate_buy_trend" function: Identifies buy opportunities based on the following conditions: Fast slope is greater than a specified value (fslope_buy). Slow slope is greater than a specified value (sslope_buy). Current close price is higher than the close price shifted by the slope length. RSI is greater than a specified value (rsi_buy). Sets the "buy" column to 1 for the corresponding buy signals. In the "populate_sell_trend" function: Identifies sell opportunities based on the following conditions: Fast slope is less than a specified value (fslope_sell). Current close price is lower than the last lowest price. Sets the "sell" column to 1 for the corresponding sell signals. The strategy uses these buy and sell signals to evaluate the performance of the trading strategy during backtesting.
startup_candle_count : 168 Recursive Analysis found no issues while using 168 startup_candle_count
stoploss: -0.9 timeframe: 4h hash(sha256): 2fed7abeacbffc4a783a349d940308949c2f5f441d9dd460e5953d688e2161d7 indicators: sy2 sy fx slowMA sy1 fastMA slow_slope rsi entryMA fy1 fast_slope last_lowest fy2 fy close low sx marketMA
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last change: 2023-06-24 10:34:28