The FreqGym_normalized strategy is a trading strategy implemented as a class called FreqGym_normalized that inherits from the IStrategy class. Here's a brief description of what the strategy does:
The populate_indicators method is responsible for adding various technical analysis (TA) indicators to the provided DataFrame. It generates features based on the raw data and merges them with informative dataframes.
The indicators are then normalized to ensure their values fall within a specific range.
The method returns a DataFrame with all the mandatory indicators for the strategy.
The populate_buy_trend method populates the buy signal for the given DataFrame based on the TA indicators. It uses a reinforcement learning (RL) model to predict the action, and assigns a value of 1 to the "buy" column if the predicted action is 0 (indicating a buy signal). The populate_sell_trend method works similarly to populate_buy_trend, but populates the sell signal instead. It predicts the action using the RL model and assigns a value of 1 to the "sell" column if the predicted action is 1 (indicating a sell signal). The FreqGym_normalizedDCA class is a subclass of FreqGym_normalized and likely represents an extension or modification of the original strategy. However, the provided code snippet doesn't include its implementation details. Overall, the strategy calculates TA indicators, normalizes them, and uses an RL model to generate buy and sell signals based on these indicators.
The indicators are then normalized to ensure their values fall within a specific range.
The method returns a DataFrame with all the mandatory indicators for the strategy.
The populate_buy_trend method populates the buy signal for the given DataFrame based on the TA indicators. It uses a reinforcement learning (RL) model to predict the action, and assigns a value of 1 to the "buy" column if the predicted action is 0 (indicating a buy signal). The populate_sell_trend method works similarly to populate_buy_trend, but populates the sell signal instead. It predicts the action using the RL model and assigns a value of 1 to the "sell" column if the predicted action is 1 (indicating a sell signal). The FreqGym_normalizedDCA class is a subclass of FreqGym_normalized and likely represents an extension or modification of the original strategy. However, the provided code snippet doesn't include its implementation details. Overall, the strategy calculates TA indicators, normalizes them, and uses an RL model to generate buy and sell signals based on these indicators.
stoploss: -0.1 timeframe: 5m hash(sha256): 23207c7fad76803d833c6c41145d46bad65c45d024bab265761a60a35689ea10 indicators: sell htsine f"aroondown_period uo f"aroonosc_period f"dx_period fastk htleadsine f"linangle_period slowd f"rsi_period bb3_lower_gt_close plus_di f"mfi_period f"plus_di_period slowk bb2_lower_gt_close f"adx_period f"willr_period buy f"stochrsi_k_period f"aroonup_period f"stochrsi_d_period minus_di f"cmo_period f"minus_di_period bop f"fisher_rsi_period
Similar Strategies: (based on used indicators)
Strategy: FreqGym_normalized_3, Similarity Score: 96.55%
Strategy: FreqGym_normalized, Similarity Score: 93.1%
last change: 2024-04-29 21:24:41