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The StochRSITEMA strategy is a trading strategy that combines multiple technical indicators to generate buy and sell signals. Here's a breakdown of what the strategy does:
In the populate_indicators method:
It calculates the Stochastic Oscillator (stoch_slow) using the specified parameters (fastk_period, slowk_period, slowd_period). It adds the slowk and slowd values of the Stochastic Oscillator to the dataframe.
It calculates the Relative Strength Index (RSI) using the specified RSI period and adds it to the dataframe.
It calculates the Triple Exponential Moving Average (TEMA) using the specified TEMA period and adds it to the dataframe.
Finally, it returns the updated dataframe. In the populate_buy_trend method: It identifies the conditions for a buy signal using the following criteria: RSI crosses above the lower band. Stochastic slowd crosses above the lower band. Stochastic slowk crosses above the lower band. Stochastic slowk crosses slowd. Volume is greater than 0. It marks the corresponding rows in the dataframe with a 'buy' signal. It returns the updated dataframe. In the populate_sell_trend method: It checks the specified trigger condition for selling (tema-trigger). If the trigger is set to 'close', it adds a condition where the close price is below the TEMA. If the trigger is set to 'both', it adds a condition where both the close and open prices are below the TEMA. If the trigger is set to 'average', it adds a condition where the average of the close and open prices is below the TEMA. It also checks that the volume is greater than 0. If any of the conditions are met, it marks the corresponding rows in the dataframe with a 'sell' signal. It returns the updated dataframe. Overall, the StochRSITEMA strategy uses the Stochastic Oscillator, RSI, and TEMA indicators to generate buy and sell signals based on specific conditions. These signals can be used for backtesting and evaluating the performance of the strategy.
It calculates the Relative Strength Index (RSI) using the specified RSI period and adds it to the dataframe.
It calculates the Triple Exponential Moving Average (TEMA) using the specified TEMA period and adds it to the dataframe.
Finally, it returns the updated dataframe. In the populate_buy_trend method: It identifies the conditions for a buy signal using the following criteria: RSI crosses above the lower band. Stochastic slowd crosses above the lower band. Stochastic slowk crosses above the lower band. Stochastic slowk crosses slowd. Volume is greater than 0. It marks the corresponding rows in the dataframe with a 'buy' signal. It returns the updated dataframe. In the populate_sell_trend method: It checks the specified trigger condition for selling (tema-trigger). If the trigger is set to 'close', it adds a condition where the close price is below the TEMA. If the trigger is set to 'both', it adds a condition where both the close and open prices are below the TEMA. If the trigger is set to 'average', it adds a condition where the average of the close and open prices is below the TEMA. It also checks that the volume is greater than 0. If any of the conditions are met, it marks the corresponding rows in the dataframe with a 'sell' signal. It returns the updated dataframe. Overall, the StochRSITEMA strategy uses the Stochastic Oscillator, RSI, and TEMA indicators to generate buy and sell signals based on specific conditions. These signals can be used for backtesting and evaluating the performance of the strategy.
stoploss: -0.25 timeframe: 5m hash(sha256): d4c4f397fc3685215590f4522d4e8286ce4d3e828cf485f83aff80a95a499d3a indicators: slowd slowk volume stochslowk tema stochslowdperiod stake_currency stochfastkperiod close rsi stochlowerband temaperiod tematrigger stochslowkperiod rsilowerband open rsiperiod stochslowd
Similar Strategies: (based on used indicators)
Strategy: StochRSITEMA, Similarity Score: 94.74%
last change: 2023-06-28 07:49:32