The SMAOffsetV2 strategy is a backtesting strategy that aims to identify buying and selling opportunities based on the Simple Moving Average (SMA) and trend detection. Here's a breakdown of its important components:
The strategy uses the '5m' timeframe for trading and the '1h' timeframe for informative data. The minimal_roi parameter sets a minimum return on investment of 1, indicating that the strategy aims to achieve at least a 1% ROI.
The stoploss parameter is set to -0.20, indicating a 20% stop loss limit.
The custom_stoploss function is implemented to customize the stop loss behavior based on specific conditions.
In this case, if the trade is open for more than 40 minutes and the current profit is below -0.1, the stop loss is set to -0.01. The informative_pairs function returns a list of pairs and their corresponding informative timeframe, which is used to gather additional data for analysis. The get_informative_indicators function calculates the Exponential Moving Average (EMA) for the informative timeframe and determines whether to go long based on the EMA crossover. The populate_indicators function populates the main dataframe with indicators such as SMA offset values. The populate_buy_trend function identifies buy signals when the 'go_long' indicator is positive, the closing price is below the SMA offset, and the volume is greater than 0. The populate_sell_trend function identifies sell signals when the 'go_long' indicator is zero or the closing price is above the SMA offset position, and the volume is greater than 0. The plot_config dictionary defines the plot colors for various indicators. Overall, the SMAOffsetV2 strategy combines SMA crossovers, trend detection, and custom stop loss to generate buy and sell signals based on the provided parameters and indicators.
The stoploss parameter is set to -0.20, indicating a 20% stop loss limit.
The custom_stoploss function is implemented to customize the stop loss behavior based on specific conditions.
In this case, if the trade is open for more than 40 minutes and the current profit is below -0.1, the stop loss is set to -0.01. The informative_pairs function returns a list of pairs and their corresponding informative timeframe, which is used to gather additional data for analysis. The get_informative_indicators function calculates the Exponential Moving Average (EMA) for the informative timeframe and determines whether to go long based on the EMA crossover. The populate_indicators function populates the main dataframe with indicators such as SMA offset values. The populate_buy_trend function identifies buy signals when the 'go_long' indicator is positive, the closing price is below the SMA offset, and the volume is greater than 0. The populate_sell_trend function identifies sell signals when the 'go_long' indicator is zero or the closing price is above the SMA offset position, and the volume is greater than 0. The plot_config dictionary defines the plot colors for various indicators. Overall, the SMAOffsetV2 strategy combines SMA crossovers, trend detection, and custom stop loss to generate buy and sell signals based on the provided parameters and indicators.
startup_candle_count : 200 Recursive Analysis found no issues while using 200 startup_candle_count
stoploss: -0.2 timeframe: 5m hash(sha256): 34e0584ebcfc856146c507a49e30684ff3eff356aef78756736f6be5e7bf2d67 indicators: go_long sma_30_offset_pos volume close ema_slow ema_fast sma_30_offset date open high low close volume
No similar strategies found. (based on used indicators)
last change: 2024-05-02 11:09:16