The MultiMA_TSL strategy is a trading strategy that uses multiple moving averages (MA) and other indicators to determine buy and sell signals. Here is a breakdown of what the strategy does:
In the populate_indicators function:
Calculates the exponential moving average (EMA) offset for buying using a specified number of candles and a low offset value. Calculates the triangular moving average (TRIMA) offset for buying using a specified number of candles and a low offset value.
Calculates the EMA offset for selling using a specified number of candles and a high offset value.
Calculates the Elder's Force Index (EWO) using the provided parameters.
Calculates the relative strength index (RSI) with a time period of 14. Calculates the fast RSI with a time period of 4. Returns the updated dataframe with these indicators. In the populate_buy_trend function: Checks if the strategy is in hyperopt run mode. If in hyperopt run mode, calculates the EMA and TRIMA offsets for buying and the EMA offset for selling using the same logic as in populate_indicators. Initializes a 'buy_tag' column in the dataframe. Sets conditions for buying based on various criteria, including: Close price being below the EMA offset for buying and meeting certain EWO and RSI conditions. Close price being below the TRIMA offset for buying and meeting certain EWO and RSI conditions. Appends the conditions to a list. Adds an additional check based on RSI and close price for buying. If there are conditions, calculates the 'buy' column by applying the conditions using a logical OR operation and the additional check using a logical AND operation. Returns the updated dataframe with the 'buy' column. In the populate_sell_trend function: Checks if the strategy is in hyperopt run mode. If in hyperopt run mode, calculates the EMA offset for selling using the same logic as in populate_indicators. Initializes a 'sell' column in the dataframe and sets it to zero. Returns the updated dataframe. Additionally, outside of the class, there is a function that calculates the difference between two exponential moving averages (sma1 and sma2) divided by the closing price and multiplied by 100. This is returned as the 'smadif' value. Overall, the strategy uses moving averages, EWO, RSI, and other conditions to generate buy and sell signals based on price and indicator movements.
Calculates the EMA offset for selling using a specified number of candles and a high offset value.
Calculates the Elder's Force Index (EWO) using the provided parameters.
Calculates the relative strength index (RSI) with a time period of 14. Calculates the fast RSI with a time period of 4. Returns the updated dataframe with these indicators. In the populate_buy_trend function: Checks if the strategy is in hyperopt run mode. If in hyperopt run mode, calculates the EMA and TRIMA offsets for buying and the EMA offset for selling using the same logic as in populate_indicators. Initializes a 'buy_tag' column in the dataframe. Sets conditions for buying based on various criteria, including: Close price being below the EMA offset for buying and meeting certain EWO and RSI conditions. Close price being below the TRIMA offset for buying and meeting certain EWO and RSI conditions. Appends the conditions to a list. Adds an additional check based on RSI and close price for buying. If there are conditions, calculates the 'buy' column by applying the conditions using a logical OR operation and the additional check using a logical AND operation. Returns the updated dataframe with the 'buy' column. In the populate_sell_trend function: Checks if the strategy is in hyperopt run mode. If in hyperopt run mode, calculates the EMA offset for selling using the same logic as in populate_indicators. Initializes a 'sell' column in the dataframe and sets it to zero. Returns the updated dataframe. Additionally, outside of the class, there is a function that calculates the difference between two exponential moving averages (sma1 and sma2) divided by the closing price and multiplied by 100. This is returned as the 'smadif' value. Overall, the strategy uses moving averages, EWO, RSI, and other conditions to generate buy and sell signals based on price and indicator movements.
startup_candle_count : 200 Recursive Analysis found no issues while using 200 startup_candle_count
stoploss: -0.15 timeframe: 5m hash(sha256): 73b4c225f2987ac04a913bb2d25033c5cbd607a01f8da734958c622eda3b51ab indicators: volume close rsi ema_offset_buy trima_offset_buy runmode ema_offset_sell ewo rsi_fast
No similar strategies found. (based on used indicators)
last change: 2024-05-02 15:59:37