The GodStra strategy is a backtesting strategy implemented as a class that inherits from the IStrategy interface. It consists of three main methods: populate_indicators, populate_buy_trend, and populate_sell_trend. The populate_indicators method takes a dataframe and a metadata dictionary as input.
It preprocesses the dataframe by removing any rows with missing values and then adds technical analysis indicators using the add_all_ta_features function.
The resulting modified dataframe is returned.
The populate_buy_trend method is responsible for populating the buy signals in the dataframe based on a set of buy parameters. It iterates over the buy parameters and retrieves the necessary values from the dataframe. It then applies a series of conditions based on the specified comparison operators (OPR) and compares the indicator values (DFIND) with other values (DFCRS, INT, REAL) as specified by the buy parameters. If the conditions are met, the corresponding buy signal is set to 1 in the dataframe. The populate_sell_trend method is similar to populate_buy_trend but handles the sell signals instead. It iterates over the sell parameters, retrieves the required values from the dataframe, and applies conditions based on comparison operators (OPR) to determine the sell signals. Overall, the GodStra strategy performs preprocessing, generates buy and sell signals based on specified conditions and parameters, and modifies the input dataframe accordingly.
It preprocesses the dataframe by removing any rows with missing values and then adds technical analysis indicators using the add_all_ta_features function.
The resulting modified dataframe is returned.
The populate_buy_trend method is responsible for populating the buy signals in the dataframe based on a set of buy parameters. It iterates over the buy parameters and retrieves the necessary values from the dataframe. It then applies a series of conditions based on the specified comparison operators (OPR) and compares the indicator values (DFIND) with other values (DFCRS, INT, REAL) as specified by the buy parameters. If the conditions are met, the corresponding buy signal is set to 1 in the dataframe. The populate_sell_trend method is similar to populate_buy_trend but handles the sell signals instead. It iterates over the sell parameters, retrieves the required values from the dataframe, and applies conditions based on comparison operators (OPR) to determine the sell signals. Overall, the GodStra strategy performs preprocessing, generates buy and sell signals based on specified conditions and parameters, and modifies the input dataframe accordingly.
stoploss: -0.345 timeframe: 12h hash(sha256): cb99bcbbee74962d038f5506d176ca880d479a08d918a8a6eaa93a4003176a8f
Was not able to fetch indicators from Strategyfile.
last change: 2024-04-29 00:40:51