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The strategy, named "Obelisk_3EMA_StochRSI_ATR," combines multiple indicators to generate trading signals. Here is a breakdown of what the strategy does:
populate_indicators():
This method populates the indicators used by the strategy. It checks if the strategy is being run in backtest or hyperopt mode and ensures that the timeframe is either 5 minutes or 1 minute.
If the timeframe matches the informative timeframe, it performs the indicator calculations on the given dataframe.
Otherwise, it retrieves the informative pair's dataframe and performs the indicator calculations on it.
The informative pair's dataframe is then merged with the original dataframe. Some columns are renamed to remove the timeframe suffix. populate_buy_trend(): This method determines the buy signals for the strategy. It sets the 'buy' column of the dataframe to 1 when the 'go_long' indicator crosses above 0. populate_sell_trend(): This method determines the sell signals for the strategy. It sets the 'sell' column of the dataframe to 0, indicating no sell signals. stoploss_from_open(): This function calculates the stop loss level based on the open price, current profit, and stop percentage. populate_stop_loss(): This method calculates the stop loss level for each trade. It retrieves custom information for the specific trading pair and checks if a take profit or stop percentage is defined. If the current rate exceeds the take profit level, a stop loss of 0.001 is returned. If a stop percentage is defined, it calculates the new stop loss level based on the current profit and the stop percentage. plot_config: This variable contains the configuration for plotting the strategy's indicators. The main plot includes the 50-day exponential moving average (ema50), 14-day exponential moving average (ema14), 8-day exponential moving average (ema8), take profit level, and stop loss level. The subplots include the Stochastic RSI (SRSI) with its 'k' and 'd' components, and the Average True Range (ATR). Overall, the strategy utilizes indicators such as exponential moving averages, Stochastic RSI, and Average True Range to generate buy and sell signals, and it also incorporates stop loss and take profit levels for risk management. The provided code snippet represents the implementation of the strategy within a class structure.
If the timeframe matches the informative timeframe, it performs the indicator calculations on the given dataframe.
Otherwise, it retrieves the informative pair's dataframe and performs the indicator calculations on it.
The informative pair's dataframe is then merged with the original dataframe. Some columns are renamed to remove the timeframe suffix. populate_buy_trend(): This method determines the buy signals for the strategy. It sets the 'buy' column of the dataframe to 1 when the 'go_long' indicator crosses above 0. populate_sell_trend(): This method determines the sell signals for the strategy. It sets the 'sell' column of the dataframe to 0, indicating no sell signals. stoploss_from_open(): This function calculates the stop loss level based on the open price, current profit, and stop percentage. populate_stop_loss(): This method calculates the stop loss level for each trade. It retrieves custom information for the specific trading pair and checks if a take profit or stop percentage is defined. If the current rate exceeds the take profit level, a stop loss of 0.001 is returned. If a stop percentage is defined, it calculates the new stop loss level based on the current profit and the stop percentage. plot_config: This variable contains the configuration for plotting the strategy's indicators. The main plot includes the 50-day exponential moving average (ema50), 14-day exponential moving average (ema14), 8-day exponential moving average (ema8), take profit level, and stop loss level. The subplots include the Stochastic RSI (SRSI) with its 'k' and 'd' components, and the Average True Range (ATR). Overall, the strategy utilizes indicators such as exponential moving averages, Stochastic RSI, and Average True Range to generate buy and sell signals, and it also incorporates stop loss and take profit levels for risk management. The provided code snippet represents the implementation of the strategy within a class structure.
stoploss: -0.99 timeframe: 5m hash(sha256): 20a3b499699bed154234a087e22b0f2df802a5f162283a442c0a306943db190a indicators: ema14 atr srsi_k go_long sell close rsi srsi_d ema8 date runmode stop_loss ema50 stop_pct date stop_pct take_profit take_profit date open high low close volume
Similar Strategies: (based on used indicators)
Strategy: Obelisk_3EMA_StochRSI_ATR, Similarity Score: 96%
Strategy: Obelisk_3EMA_StochRSI_ATR_259, Similarity Score: 96%
last change: 2022-07-02 19:54:08