The MultiRSICMF strategy is a trading strategy that uses a combination of technical indicators, including the Relative Strength Index (RSI) and the Chaikin Money Flow (CMF), to determine buy and sell signals. Here's a breakdown of what the strategy does:
The strategy calculates the Simple Moving Average (SMA) for two time periods: 5 and 200. It resamples the dataframes to shorter and longer intervals based on the ticker interval defined in the strategy.
The RSI and CMF are computed for the resampled dataframes.
Additionally, an oscillator indicator is calculated for the shorter interval dataframe.
The dataframes are merged back together. Any missing values (NaN) are filled with the previous values. The populate_buy_trend function determines the buy signal based on the following conditions: The 5-period SMA is greater than or equal to the 200-period SMA. The RSI is below the RSI of the longer interval dataframe minus 20. The CMF of the longer interval dataframe is greater than 0. The populate_sell_trend function determines the sell signal based on the following condition: The RSI is higher than both the RSI of the shorter interval dataframe and the RSI of the longer interval dataframe. Overall, this strategy aims to identify bullish trends by considering the relationship between SMAs, RSI levels, and CMF values, and it generates buy and sell signals accordingly.
The RSI and CMF are computed for the resampled dataframes.
Additionally, an oscillator indicator is calculated for the shorter interval dataframe.
The dataframes are merged back together. Any missing values (NaN) are filled with the previous values. The populate_buy_trend function determines the buy signal based on the following conditions: The 5-period SMA is greater than or equal to the 200-period SMA. The RSI is below the RSI of the longer interval dataframe minus 20. The CMF of the longer interval dataframe is greater than 0. The populate_sell_trend function determines the sell signal based on the following condition: The RSI is higher than both the RSI of the shorter interval dataframe and the RSI of the longer interval dataframe. Overall, this strategy aims to identify bullish trends by considering the relationship between SMAs, RSI levels, and CMF values, and it generates buy and sell signals accordingly.
stoploss: -0.05 timeframe: 5m hash(sha256): 2ab4cd8c7b6dcf450718db24f77b446f7fb4f146bcd218479231a696605a057e indicators: sma5 _shortosc cm _long _short _shortrsi rsi _longrsi _shortcmf _longcmf _longosc osc sma200
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last change: 2024-04-28 09:32:16