The SagesFreqGym strategy is designed to backtest trading strategies using technical analysis (TA) indicators. The strategy consists of three main functions:
populate_indicators: This function calculates various TA indicators for the given DataFrame, such as weighted moving averages (WMA), relative strength index (RSI), and relative volatility index (RVI). The indicators are added as additional columns to the DataFrame.
populate_buy_trend: Based on the calculated TA indicators, this function populates the buy signal for the DataFrame.
It uses an RL model to predict the action to take, and assigns a value of 1 to the "buy" column if the predicted action is a buy.
populate_sell_trend: Similar to populate_buy_trend, this function populates the sell signal for the DataFrame based on the TA indicators and the RL model's predictions. It assigns a value of 1 to the "sell" column if the predicted action is a sell. Additionally, the strategy includes code to generate output for the backtesting results. It initializes an output DataFrame with zeros, processes the indicators for the specified window size, and uses a prediction function to generate the results. Overall, the strategy aims to leverage TA indicators and an RL model to generate buy and sell signals for trading.
populate_buy_trend: Based on the calculated TA indicators, this function populates the buy signal for the DataFrame.
It uses an RL model to predict the action to take, and assigns a value of 1 to the "buy" column if the predicted action is a buy.
populate_sell_trend: Similar to populate_buy_trend, this function populates the sell signal for the DataFrame based on the TA indicators and the RL model's predictions. It assigns a value of 1 to the "sell" column if the predicted action is a sell. Additionally, the strategy includes code to generate output for the backtesting results. It initializes an output DataFrame with zeros, processes the indicators for the specified window size, and uses a prediction function to generate the results. Overall, the strategy aims to leverage TA indicators and an RL model to generate buy and sell signals for trading.
stoploss: -0.99 timeframe: 5m hash(sha256): 698975ba7cc00ae2308ec79341028972c70d9dff0fd427f4828b22f49b8311bc indicators: rvi_period sell wma_period volume rsi_period buy volume_roc
No similar strategies found. (based on used indicators)
last change: 2024-04-29 02:53:38