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The "Combined_NFIv7_SMA" strategy is designed for backtesting trading strategies. It consists of two main components: indicator population and buy trend determination. In the "populate_indicators" method, the strategy populates various indicators based on the provided dataframe and metadata.
It retrieves informative indicators on a 1-hour timeframe and merges them with the current timeframe indicators.
The resulting dataframe is then returned.
The "populate_buy_trend" method determines the buy conditions for the strategy. It defines a set of conditions using logical operations and various indicators. These conditions include checks on RSI values, uptrend indicators, moving averages, volume, and other technical indicators. The logic for each buy condition is stored in separate variables (buy_01_logic, buy_02_logic, buy_03_logic), which are combined using logical AND operations. Additional buy protections can be enabled or disabled based on user-defined settings. The final buy conditions are stored in the 'buy_01_trigger', 'buy_02_trigger', and 'buy_03_trigger' columns of the dataframe, depending on the enabled buy conditions. The strategy supports multiple buy conditions, and the user can configure the parameters for each condition. Please note that the provided code snippet seems to be incomplete, as it cuts off in the middle of the last buy condition.
It retrieves informative indicators on a 1-hour timeframe and merges them with the current timeframe indicators.
The resulting dataframe is then returned.
The "populate_buy_trend" method determines the buy conditions for the strategy. It defines a set of conditions using logical operations and various indicators. These conditions include checks on RSI values, uptrend indicators, moving averages, volume, and other technical indicators. The logic for each buy condition is stored in separate variables (buy_01_logic, buy_02_logic, buy_03_logic), which are combined using logical AND operations. Additional buy protections can be enabled or disabled based on user-defined settings. The final buy conditions are stored in the 'buy_01_trigger', 'buy_02_trigger', and 'buy_03_trigger' columns of the dataframe, depending on the enabled buy conditions. The strategy supports multiple buy conditions, and the user can configure the parameters for each condition. Please note that the provided code snippet seems to be incomplete, as it cuts off in the middle of the last buy condition.
stoploss: -0.99 timeframe: 5m hash(sha256): 062f3d84d7aa9c6dff790040c64c9a204ae66df779a40f292ff22245199ae47a
Was not able to fetch indicators from Strategyfile.
last change: 2022-07-02 19:54:08