The "GodStra" strategy is a trading strategy implemented as a class that inherits from the "IStrategy" interface. It performs backtesting and includes methods for populating indicators, determining buy signals, and determining sell signals. In the "populate_indicators" method, the strategy takes a DataFrame of historical price data and adds technical analysis indicators to it using the "add_all_ta_features" function.
This function calculates various indicators such as moving averages, relative strength index (RSI), and others based on the provided OHLCV (open, high, low, close, volume) data.
The "populate_buy_trend" method generates buy signals based on a set of parameters defined in the strategy.
It iterates over the buy parameters and checks conditions based on the specified operator (OPR) and indicators (IND and CRS). Depending on the operator, it compares the values of the indicators and adds conditions to the list. The method then applies the conditions to the DataFrame, assigning a value of 1 to the "buy" column for rows that satisfy all the conditions. The "populate_sell_trend" method is similar to "populate_buy_trend" but generates sell signals. It iterates over the sell parameters, checks conditions, and assigns a value of 1 to the "sell" column for rows that satisfy all the conditions. Both the buy and sell methods use the "reduce" function to combine the conditions using a logical AND operation, ensuring that all conditions must be met for a signal to be generated. Overall, this strategy calculates technical indicators, generates buy and sell signals based on specified parameters and indicator values, and assigns values to the "buy" and "sell" columns of the DataFrame to indicate trading signals.
This function calculates various indicators such as moving averages, relative strength index (RSI), and others based on the provided OHLCV (open, high, low, close, volume) data.
The "populate_buy_trend" method generates buy signals based on a set of parameters defined in the strategy.
It iterates over the buy parameters and checks conditions based on the specified operator (OPR) and indicators (IND and CRS). Depending on the operator, it compares the values of the indicators and adds conditions to the list. The method then applies the conditions to the DataFrame, assigning a value of 1 to the "buy" column for rows that satisfy all the conditions. The "populate_sell_trend" method is similar to "populate_buy_trend" but generates sell signals. It iterates over the sell parameters, checks conditions, and assigns a value of 1 to the "sell" column for rows that satisfy all the conditions. Both the buy and sell methods use the "reduce" function to combine the conditions using a logical AND operation, ensuring that all conditions must be met for a signal to be generated. Overall, this strategy calculates technical indicators, generates buy and sell signals based on specified parameters and indicator values, and assigns values to the "buy" and "sell" columns of the DataFrame to indicate trading signals.
stoploss: -0.345 timeframe: 12h hash(sha256): 70294cee8c3bc938e04d0821a7095abc04ec7b1c4f2d6cbf9a9ef39fe460a4af
Was not able to fetch indicators from Strategyfile.
last change: 2024-04-28 23:47:00