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May 30, 2024 10:34
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| { | |
| "Advanced_Risk_Management_Techniques": { | |
| "Cross-Validation_and_Backtesting": { | |
| "Ensures_Data_Integrity_and_Prevents_Overfitting": "Cross-validation divides data into subsets to validate model performance, while backtesting tests strategies on historical data to ensure robustness." | |
| }, | |
| "Dynamic_Hedging_and_Adaptation": { | |
| "Adjusts_Positions_Continuously_for_Desired_Risk_Levels_Enhancing_Adaptability": "Dynamic hedging involves continuously adjusting positions to manage risk effectively." | |
| }, | |
| "Ensemble_Methods": { | |
| "Bagging_Boosting_Stacking_to_Improve_Robustness_and_Reduce_Overfitting": "Ensemble methods combine multiple models to enhance prediction accuracy and robustness." | |
| }, | |
| "Regular_Updates_and_Retraining": { | |
| "Keeps_Models_Relevant_to_Current_Market_Conditions_Preventing_Overfitting_to_Outdated_Data": "Regularly updating and retraining models ensures they remain effective under changing market conditions." | |
| }, | |
| "Regularization_Techniques": { | |
| "L1_L2_Regularization_to_Simplify_Models_Enhancing_Generalization": "Regularization techniques prevent overfitting by penalizing complex models, promoting simplicity and better generalization." | |
| }, | |
| "Risk_Parity_and_Diversification": { | |
| "Allocates_Risk_Equally_Promoting_Diversification_and_Reducing_Specific_Asset_Risk": "This technique aims for a balanced risk distribution across the portfolio." | |
| }, | |
| "Stress_Testing_and_Scenario_Analysis": { | |
| "Simulates_Extreme_Conditions_to_Evaluate_Strategy_Resilience": "These techniques test the robustness of trading strategies under extreme market conditions." | |
| } | |
| }, | |
| "Data_Preprocessing": { | |
| "Cleaning_Techniques": { | |
| "Accuracy": "Ensuring that the data is free from errors, which is crucial for making reliable predictions. Techniques include removing or correcting erroneous values and outliers.", | |
| "Completeness": "Making sure that the dataset contains all necessary information without missing values. Methods include filling missing values using statistical methods like mean, median, or mode imputation." | |
| }, | |
| "Feature_Encoding": { | |
| "Interpretability": "Transforming categorical data into a numerical format that is understandable by machine learning models. Techniques include one-hot encoding and label encoding.", | |
| "Representation": "Ensuring that the encoded data maintains the original meaning and relationships of the categories." | |
| }, | |
| "Feature_Scaling": { | |
| "Consistency": "Standardizing the range of independent variables to ensure that each feature contributes equally to the analysis. Techniques like min-max scaling and standardization are commonly used.", | |
| "Normalization": "Adjusting the data to a common scale without distorting differences in the ranges of values. This helps in speeding up the convergence of learning algorithms." | |
| } | |
| }, | |
| "Dependency_Mapping": { | |
| "Adaptability_and_Learning_Efficiency": { | |
| "Supported_by_Ensemble_Methods_Dynamic_Hedging_and_Adaptation_and_Regular_Updates_and_Retraining": "These methods enhance the adaptability and robustness of models, ensuring they remain effective." | |
| }, | |
| "Data_Accuracy_and_Completeness": { | |
| "Supported_by_Cross-Validation_and_Backtesting": "These techniques ensure the integrity and validation of data used in models." | |
| }, | |
| "Reward_Optimization": { | |
| "Supported_by_Risk_Parity_and_Diversification": "Balancing risk across the portfolio helps in optimizing rewards by minimizing potential losses and ensuring steady gains." | |
| }, | |
| "Robustness_and_Generalization": { | |
| "Supported_by_Cross-Validation_and_Backtesting_Regularization_Techniques_Ensemble_Methods_and_Stress_Testing_and_Scenario_Analysis": "These techniques collectively ensure that models perform well and generalize to new data without overfitting." | |
| }, | |
| "Trend_Identification_and_Signal_Strength": { | |
| "Indirectly_Benefits_from_Techniques_Ensuring_Robust_Model_Performance": "Robust models help in accurately identifying trends and signals." | |
| } | |
| }, | |
| "Feature_Engineering": { | |
| "Advanced_Feature_Generation": { | |
| "Dimensionality_Reduction": "Techniques like PCA (Principal Component Analysis) and t-SNE (t-distributed Stochastic Neighbor Embedding) are used to reduce the number of features while retaining essential information.", | |
| "Latent_Features": "Extracting hidden features using methods like autoencoders to uncover underlying patterns in the data." | |
| }, | |
| "Statistical_Features": { | |
| "Predictive_Power": "Identifying features that have a strong correlation with the target variable and are likely to improve model predictions.", | |
| "Variability": "Creating features that capture the variability within the data, such as standard deviation, variance, and range." | |
| }, | |
| "Technical_Indicators": { | |
| "Signal_Strength": "Measuring the strength of signals provided by technical indicators to make informed trading decisions.", | |
| "Trend_Identification": "Utilizing indicators like moving averages, MACD, and Bollinger Bands to identify market trends." | |
| } | |
| }, | |
| "Machine_Learning_Models": { | |
| "LSTM/GRU": { | |
| "Memory_Retention": "These models retain information over long sequences, making them suitable for time series prediction.", | |
| "Temporal_Dynamics": "Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) are designed to capture temporal dependencies in sequential data." | |
| }, | |
| "Neural_Networks": { | |
| "Adaptability": "Neural networks can learn complex patterns and adapt to different types of data.", | |
| "Learning_Efficiency": "Advanced architectures and training techniques enhance the efficiency of learning from data." | |
| }, | |
| "Random_Forest": { | |
| "Feature_Importance": "Providing insights into the importance of different features through the aggregated decision trees.", | |
| "Robustness": "Combining multiple decision trees to improve model stability and reduce overfitting." | |
| }, | |
| "SVM": { | |
| "Generalization": "SVMs are effective in generalizing well to unseen data by finding an optimal hyperplane.", | |
| "Margin_Maximization": "Support Vector Machines aim to maximize the margin between different classes for better separation." | |
| }, | |
| "XGBoost": { | |
| "Boosting": "An ensemble technique that combines the predictions of several weak learners to form a strong learner.", | |
| "Precision": "XGBoost is known for its high precision and efficiency in handling large datasets." | |
| } | |
| }, | |
| "Risk_Management_Techniques": { | |
| "Conditional_Value_at_Risk_(CVaR)": { | |
| "Average_Loss_Beyond_VaR": "CVaR provides an average loss measure for losses that exceed the VaR threshold." | |
| }, | |
| "Dynamic_Hedging": { | |
| "Continuous_Risk_Protection_Adjustment": "Adjusting hedge positions dynamically to maintain desired risk levels in response to market changes." | |
| }, | |
| "Machine_Learning-Based_Models": { | |
| "Predictive_Risk_Analysis": "Using machine learning models to predict potential risks and adjust strategies accordingly." | |
| }, | |
| "Risk_Parity": { | |
| "Equal_Risk_Distribution_Across_Assets": "Risk parity focuses on distributing risk equally across various assets to achieve a balanced portfolio." | |
| }, | |
| "Stress_Testing": { | |
| "Evaluating_Extreme_Market_Conditions": "Stress testing involves simulating extreme scenarios to assess the resilience of trading strategies." | |
| }, | |
| "Value_at_Risk_(VaR)": { | |
| "Max_Potential_Loss_Estimation": "VaR estimates the maximum potential loss over a specified time period with a given confidence level." | |
| } | |
| }, | |
| "Trade_Execution_and_RL_Environment": { | |
| "Integration_Points": [ | |
| { | |
| "Signal_Generation_to_Environment_Setup": { | |
| "Subcomponents": [ | |
| { | |
| "Technical_Indicators": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": 0.9, | |
| "Simple_Moving_Average": 20 | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30 | |
| } | |
| } | |
| }, | |
| { | |
| "State_Space": { | |
| "Price_Data": { | |
| "Adjustments": true, | |
| "Frequency": "1min", | |
| "Time_Frame": 60 | |
| }, | |
| "Technical_Indicators": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Smoothing_Factor": 0.9 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30 | |
| } | |
| } | |
| } | |
| } | |
| ] | |
| } | |
| } | |
| ] | |
| }, | |
| "Training_Algorithms": { | |
| "DQN": { | |
| "Exploration_vs_Exploitation": "Balancing the trade-off between exploring new actions and exploiting known ones to maximize rewards.", | |
| "Reward_Optimization": "Deep Q-Networks (DQN) optimize the expected cumulative reward through reinforcement learning." | |
| } | |
| }, | |
| "latent_dependency_map_trading_ml": { | |
| "RL_Gym_MTSim": { | |
| "Environment_Setup": { | |
| "Action_Space": { | |
| "Buy": { | |
| "Execution_Price": 100.0, | |
| "Signal_Strength": 0.8 | |
| }, | |
| "Sell": { | |
| "Execution_Price": 95.0, | |
| "Signal_Strength": -0.6 | |
| } | |
| }, | |
| "Reward_Function": { | |
| "Profit_and_Loss": { | |
| "Calculation_Method": "mean", | |
| "Time_Frame": 60 | |
| }, | |
| "Risk_Adjusted_Returns": { | |
| "Sharpe_Ratio_Adjusted": 1.5, | |
| "Sortino_Ratio": 2.0 | |
| } | |
| }, | |
| "State_Space": { | |
| "Advanced_Feature_Generation": { | |
| "Autoencoders": { | |
| "Encoded_Features": { | |
| "Encoder_Architecture": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 64 | |
| ], | |
| "Input_Layer": 256, | |
| "Latent_Space": 32 | |
| }, | |
| "Training_Parameters": { | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01 | |
| } | |
| } | |
| }, | |
| "Fourier_Transforms": { | |
| "FFT_Coefficients": { | |
| "Amplitude": [ | |
| 0.4, | |
| 0.3, | |
| 0.2, | |
| 0.1 | |
| ], | |
| "Frequency_Bands": [ | |
| 0, | |
| 5, | |
| 10, | |
| 20 | |
| ], | |
| "Phase": [ | |
| 0.1, | |
| 0.2, | |
| 0.3, | |
| 0.4 | |
| ] | |
| } | |
| }, | |
| "Principal_Component_Analysis": { | |
| "PCA_Components": { | |
| "Explained_Variance_Ratio": [ | |
| 0.5, | |
| 0.3, | |
| 0.2 | |
| ], | |
| "Number_of_Components": 3 | |
| } | |
| }, | |
| "Wavelet_Transforms": { | |
| "Wavelet_Coefficients": { | |
| "Approximation_Coefficients": [ | |
| 0.6, | |
| 0.4 | |
| ], | |
| "Decomposition_Level": 2, | |
| "Detail_Coefficients": [ | |
| 0.2, | |
| 0.3 | |
| ], | |
| "Wavelet_Type": "db4" | |
| } | |
| } | |
| }, | |
| "Feature_Generation": { | |
| "Statistical_Features": { | |
| "Kurtosis": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Median": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Skewness": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Standard_Deviation": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| }, | |
| "Technical_Indicator_Features": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| }, | |
| "Time_Series_Features": { | |
| "Lagged_Values": { | |
| "Include_Current": true, | |
| "Lags": [ | |
| 1, | |
| 5, | |
| 10, | |
| 20 | |
| ] | |
| }, | |
| "Rolling_Window_Statistics": { | |
| "Rolling_Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Rolling_Std": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Price_Data": { | |
| "Adjustments": true, | |
| "Frequency": "1min", | |
| "Time_Frame": 60 | |
| }, | |
| "Technical_Indicators": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Simulation_Data": { | |
| "Historical_Price_Data": { | |
| "Data_Cleaning": { | |
| "Data_Normalization": { | |
| "Method": "min-max", | |
| "Parameters": [ | |
| 0, | |
| 1 | |
| ] | |
| }, | |
| "Missing_Data_Handling": { | |
| "Method": "interpolation", | |
| "Parameters": "linear" | |
| }, | |
| "Outlier_Removal": { | |
| "Method": "z-score", | |
| "Parameters": 3 | |
| } | |
| }, | |
| "Data_Sources": { | |
| "Source_1": { | |
| "Format": "csv", | |
| "Frequency": "1min", | |
| "Type": "price" | |
| }, | |
| "Source_2": { | |
| "Format": "json", | |
| "Frequency": "1day", | |
| "Type": "fundamental" | |
| } | |
| } | |
| }, | |
| "Synthetic_Data": { | |
| "Data_Generation_Methods": { | |
| "GAN": { | |
| "Architecture": { | |
| "Discriminator": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 64 | |
| ], | |
| "Input_Layer": 256, | |
| "Output_Layer": 1 | |
| }, | |
| "Generator": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 256 | |
| ], | |
| "Input_Layer": 100, | |
| "Output_Layer": 256 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01 | |
| } | |
| }, | |
| "Monte_Carlo_Simulation": { | |
| "Drift": 0.01, | |
| "Number_of_Simulations": 1000, | |
| "Time_Step": 1, | |
| "Volatility": 0.02 | |
| } | |
| } | |
| } | |
| }, | |
| "Training_Algorithm": { | |
| "A2C": { | |
| "Network_Architecture": { | |
| "Actor_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "softmax", | |
| "Number_of_Neurons": 3 | |
| } | |
| }, | |
| "Critic_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 1 | |
| } | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Discount_Factor": 0.99, | |
| "Entropy_Coefficient": 0.01, | |
| "Learning_Rate": 0.01, | |
| "Value_Loss_Coefficient": 0.5 | |
| } | |
| }, | |
| "DQN": { | |
| "Network_Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 3 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Discount_Factor": 0.95, | |
| "Exploration_Rate": 0.1, | |
| "Learning_Rate": 0.01, | |
| "Replay_Buffer_Size": 100000 | |
| } | |
| }, | |
| "PPO": { | |
| "Policy_Architecture": { | |
| "Actor_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "softmax", | |
| "Number_of_Neurons": 3 | |
| } | |
| }, | |
| "Critic_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 1 | |
| } | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Clip_Range": 0.2, | |
| "Entropy_Coefficient": 0.0, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Value_Loss_Coefficient": 0.5 | |
| } | |
| } | |
| } | |
| }, | |
| "Trade_Execution": { | |
| "Signal_Generation": { | |
| "Advanced_Feature_Generation": { | |
| "Autoencoders": { | |
| "Encoded_Features": { | |
| "Encoder_Architecture": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 64 | |
| ], | |
| "Input_Layer": 256, | |
| "Latent_Space": 32 | |
| }, | |
| "Training_Parameters": { | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01 | |
| } | |
| } | |
| }, | |
| "Fourier_Transforms": { | |
| "FFT_Coefficients": { | |
| "Amplitude": [ | |
| 0.4, | |
| 0.3, | |
| 0.2, | |
| 0.1 | |
| ], | |
| "Frequency_Bands": [ | |
| 0, | |
| 5, | |
| 10, | |
| 20 | |
| ], | |
| "Phase": [ | |
| 0.1, | |
| 0.2, | |
| 0.3, | |
| 0.4 | |
| ] | |
| } | |
| }, | |
| "Principal_Component_Analysis": { | |
| "PCA_Components": { | |
| "Explained_Variance_Ratio": [ | |
| 0.5, | |
| 0.3, | |
| 0.2 | |
| ], | |
| "Number_of_Components": 3 | |
| } | |
| }, | |
| "Wavelet_Transforms": { | |
| "Wavelet_Coefficients": { | |
| "Approximation_Coefficients": [ | |
| 0.6, | |
| 0.4 | |
| ], | |
| "Decomposition_Level": 2, | |
| "Detail_Coefficients": [ | |
| 0.2, | |
| 0.3 | |
| ], | |
| "Wavelet_Type": "db4" | |
| } | |
| } | |
| }, | |
| "Feature_Generation": { | |
| "Statistical_Features": { | |
| "Kurtosis": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Median": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Skewness": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Standard_Deviation": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| }, | |
| "Technical_Indicator_Features": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| }, | |
| "Time_Series_Features": { | |
| "Lagged_Values": { | |
| "Include_Current": true, | |
| "Lags": [ | |
| 1, | |
| 5, | |
| 10, | |
| 20 | |
| ] | |
| }, | |
| "Rolling_Window_Statistics": { | |
| "Rolling_Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Rolling_Std": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Machine_Learning_Models": { | |
| "GRU": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "sigmoid", | |
| "Number_of_Neurons": 1 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Optimizer": "adam" | |
| } | |
| }, | |
| "LSTM": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "sigmoid", | |
| "Number_of_Neurons": 1 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Optimizer": "adam" | |
| } | |
| }, | |
| "Neural_Networks": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "sigmoid", | |
| "Number_of_Neurons": 1 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Optimizer": "adam" | |
| } | |
| }, | |
| "Random_Forest": { | |
| "Feature_Importance": [ | |
| 0.3, | |
| 0.2, | |
| 0.15, | |
| 0.1, | |
| 0.05 | |
| ], | |
| "Max_Depth": { | |
| "Max_Depth": 10, | |
| "Min_Depth": 2 | |
| }, | |
| "Number_of_Trees": { | |
| "Max_Trees": 500, | |
| "Min_Trees": 50 | |
| } | |
| }, | |
| "SVM": { | |
| "Kernel": { | |
| "Parameters": [ | |
| 0.1, | |
| 1, | |
| 10 | |
| ], | |
| "Type": "rbf" | |
| }, | |
| "Regularization": { | |
| "C_Value": 1.0, | |
| "Kernel_Coefficient": 0.1 | |
| } | |
| }, | |
| "XGBoost": { | |
| "Parameters": { | |
| "Colsample_Bytree": 0.8, | |
| "Gamma": 0.0, | |
| "Learning_Rate": 0.01, | |
| "Max_Depth": 6, | |
| "Min_Child_Weight": 1, | |
| "Number_of_Trees": 100, | |
| "Scale_Pos_Weight": 1, | |
| "Subsample": 0.8 | |
| } | |
| } | |
| }, | |
| "Signal_Validation": { | |
| "Backtesting": { | |
| "Historical_Data_Period": { | |
| "End_Date": "2023-01-01", | |
| "Start_Date": "2020-01-01" | |
| }, | |
| "Performance_Metrics": { | |
| "Max_Drawdown": { | |
| "Calculation_Method": "mean" | |
| }, | |
| "Return_on_Investment": { | |
| "Calculation_Method": "mean" | |
| }, | |
| "Sharpe_Ratio": { | |
| "Calculation_Method": "mean" | |
| }, | |
| "Volatility": { | |
| "Calculation_Method": "mean" | |
| } | |
| } | |
| }, | |
| "Paper_Trading": { | |
| "Execution_Speed": { | |
| "Real_Time": true, | |
| "Simulated_Time": false | |
| }, | |
| "Virtual_Capital": { | |
| "Currency": "USD", | |
| "Initial_Capital": 10000 | |
| } | |
| } | |
| }, | |
| "Technical_Indicators": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Trade_Execution_and_RL_Environment": { | |
| "Integration_Points": [ | |
| { | |
| "Signal_Generation_to_Environment_Setup": { | |
| "Components": [ | |
| "Technical_Indicators", | |
| "State_Space" | |
| ], | |
| "Description": "Using signal generation methods to define the state and action space in the RL environment.", | |
| "Subcomponents": [ | |
| { | |
| "Technical_Indicators": [ | |
| { | |
| "Moving_Averages": { | |
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| "Simple_Moving_Average": {} | |
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| { | |
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| { | |
| "MACD": { | |
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| "Histogram": { | |
| "Negative": {}, | |
| "Positive": {} | |
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| "Signal_Line": {}, | |
| "Slow_Period": {} | |
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| { | |
| "Bollinger_Bands": { | |
| "Lower_Band": {}, | |
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| "Period": {}, | |
| "Standard_Deviation_Multiplier": {}, | |
| "Upper_Band": {} | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "State_Space": [ | |
| { | |
| "Price_Data": { | |
| "Adjustments": {}, | |
| "Frequency": {}, | |
| "Time_Frame": {} | |
| } | |
| }, | |
| { | |
| "Technical_Indicators": { | |
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| "Lower_Band": {}, | |
| "Middle_Band": {}, | |
| "Period": {}, | |
| "Standard_Deviation_Multiplier": {}, | |
| "Upper_Band": {} | |
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| "Histogram": { | |
| "Negative": {}, | |
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| }, | |
| "Signal_Line": {}, | |
| "Slow_Period": {} | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": {}, | |
| "Smoothing_Factor": {} | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": {}, | |
| "Period": {} | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": {}, | |
| "Oversold_Level": {}, | |
| "Period": {} | |
| } | |
| } | |
| } | |
| ] | |
| } | |
| ] | |
| } | |
| }, | |
| { | |
| "Feature_Generation_and_Advanced_Feature_Generation_to_Training_Algorithm": { | |
| "Components": [ | |
| "Feature_Generation", | |
| "Advanced_Feature_Generation", | |
| "Training_Algorithm" | |
| ], | |
| "Description": "Enhancing training algorithms with advanced feature generation techniques.", | |
| "Subcomponents": [ | |
| { | |
| "Feature_Generation": [ | |
| { | |
| "Statistical_Features": { | |
| "Kurtosis": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| }, | |
| "Mean": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| }, | |
| "Median": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| }, | |
| "Skewness": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| }, | |
| "Standard_Deviation": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| } | |
| } | |
| }, | |
| { | |
| "Time_Series_Features": { | |
| "Lagged_Values": { | |
| "Include_Current": {}, | |
| "Lags": {} | |
| }, | |
| "Rolling_Window_Statistics": { | |
| "Rolling_Mean": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| }, | |
| "Rolling_Std": { | |
| "Calculation_Method": {}, | |
| "Window_Size": {} | |
| } | |
| } | |
| } | |
| }, | |
| { | |
| "Technical_Indicator_Features": { | |
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| "Lower_Band": {}, | |
| "Middle_Band": {}, | |
| "Period": {}, | |
| "Standard_Deviation_Multiplier": {}, | |
| "Upper_Band": {} | |
| }, | |
| "MACD": { | |
| "Fast_Period": {}, | |
| "Histogram": { | |
| "Negative": {}, | |
| "Positive": {} | |
| }, | |
| "Signal_Line": {}, | |
| "Slow_Period": {} | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": {}, | |
| "Smoothing_Factor": {} | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": {}, | |
| "Period": {} | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": {}, | |
| "Oversold_Level": {}, | |
| "Period": {} | |
| } | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "Advanced_Feature_Generation": [ | |
| { | |
| "Fourier_Transforms": { | |
| "FFT_Coefficients": { | |
| "Amplitude": {}, | |
| "Frequency_Bands": {}, | |
| "Phase": {} | |
| } | |
| } | |
| }, | |
| { | |
| "Wavelet_Transforms": { | |
| "Wavelet_Coefficients": { | |
| "Approximation_Coefficients": {}, | |
| "Decomposition_Level": {}, | |
| "Detail_Coefficients": {}, | |
| "Wavelet_Type": {} | |
| } | |
| } | |
| }, | |
| { | |
| "Principal_Component_Analysis": { | |
| "PCA_Components": { | |
| "Explained_Variance_Ratio": {}, | |
| "Number_of_Components": {} | |
| } | |
| } | |
| }, | |
| { | |
| "Autoencoders": { | |
| "Encoded_Features": { | |
| "Encoder_Architecture": { | |
| "Hidden_Layers": {}, | |
| "Input_Layer": {}, | |
| "Latent_Space": {} | |
| }, | |
| "Training_Parameters": { | |
| "Epochs": {}, | |
| "Learning_Rate": {} | |
| } | |
| } | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "Training_Algorithm": [ | |
| { | |
| "DQN": { | |
| "Network_Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": {}, | |
| "Discount_Factor": {}, | |
| "Exploration_Rate": {}, | |
| "Learning_Rate": {}, | |
| "Replay_Buffer_Size": {} | |
| } | |
| } | |
| }, | |
| { | |
| "PPO": { | |
| "Policy_Architecture": { | |
| "Actor_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Critic_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": {}, | |
| "Clip_Range": {}, | |
| "Entropy_Coefficient": {}, | |
| "Epochs": {}, | |
| "Learning_Rate": {}, | |
| "Value_Loss_Coefficient": {} | |
| } | |
| } | |
| }, | |
| { | |
| "A2C": { | |
| "Network_Architecture": { | |
| "Actor_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Critic_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": {}, | |
| "Discount_Factor": {}, | |
| "Entropy_Coefficient": {}, | |
| "Learning_Rate": {}, | |
| "Value_Loss_Coefficient": {} | |
| } | |
| } | |
| } | |
| ] | |
| } | |
| ] | |
| } | |
| }, | |
| { | |
| "ML_Models_and_Training_Algorithm": { | |
| "Components": [ | |
| "Machine_Learning_Models", | |
| "Training_Algorithm" | |
| ], | |
| "Description": "Training machine learning models with RL algorithms to enhance trade execution strategies.", | |
| "Subcomponents": [ | |
| { | |
| "Machine_Learning_Models": [ | |
| { | |
| "SVM": { | |
| "Kernel": { | |
| "Parameters": {}, | |
| "Type": {} | |
| }, | |
| "Regularization": { | |
| "C_Value": {}, | |
| "Kernel_Coefficient": {} | |
| } | |
| } | |
| }, | |
| { | |
| "Random_Forest": { | |
| "Feature_Importance": {}, | |
| "Max_Depth": { | |
| "Max_Depth": {}, | |
| "Min_Depth": {} | |
| }, | |
| "Number_of_Trees": { | |
| "Max_Trees": {}, | |
| "Min_Trees": {} | |
| } | |
| } | |
| }, | |
| { | |
| "Neural_Networks": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": {}, | |
| "Epochs": {}, | |
| "Learning_Rate": {}, | |
| "Optimizer": {} | |
| } | |
| } | |
| }, | |
| { | |
| "LSTM": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": {}, | |
| "Epochs": {}, | |
| "Learning_Rate": {}, | |
| "Optimizer": {} | |
| } | |
| } | |
| }, | |
| { | |
| "GRU": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": {}, | |
| "Number_of_Neurons": {} | |
| } | |
| }, | |
| "Input_Layer": { | |
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| }, | |
| "Output_Layer": { | |
| "Activation_Function": {}, | |
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| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": {}, | |
| "Epochs": {}, | |
| "Learning_Rate": {}, | |
| "Optimizer": {} | |
| } | |
| } | |
| }, | |
| { | |
| "XGBoost": { | |
| "Parameters": { | |
| "Colsample_Bytree": {}, | |
| "Gamma": {}, | |
| "Learning_Rate": {}, | |
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| "Min_Child_Weight": {}, | |
| "Number_of_Trees": {}, | |
| "Scale_Pos_Weight": {}, | |
| "Subsample": {} | |
| } | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "Training_Algorithm": [ | |
| { | |
| "DQN": { | |
| "Network_Architecture": "Input" | |
| } | |
| } | |
| ] | |
| } | |
| ] | |
| } | |
| } | |
| ], | |
| "Post_Conditions": { | |
| "Risk_Management_Strategies": { | |
| "Position_Sizing": { | |
| "Portfolio_Risk": {}, | |
| "Risk_Per_Trade": {} | |
| }, | |
| "Stop_Loss_Orders": { | |
| "Execution_Timings": {}, | |
| "Order_Types": {} | |
| }, | |
| "Take_Profit_Orders": { | |
| "Execution_Timings": {}, | |
| "Order_Types": {} | |
| } | |
| } | |
| }, | |
| "RL_Gym_MTSim": { | |
| "Environment_Setup": { | |
| "Action_Space": { | |
| "Buy": { | |
| "Execution_Price": 100.0, | |
| "Signal_Strength": 0.8 | |
| }, | |
| "Sell": { | |
| "Execution_Price": 95.0, | |
| "Signal_Strength": -0.6 | |
| } | |
| }, | |
| "Reward_Function": { | |
| "Profit_and_Loss": { | |
| "Calculation_Method": "mean", | |
| "Time_Frame": 60 | |
| }, | |
| "Risk_Adjusted_Returns": { | |
| "Sharpe_Ratio_Adjusted": 1.5, | |
| "Sortino_Ratio": 2.0 | |
| } | |
| }, | |
| "State_Space": { | |
| "Advanced_Feature_Generation": { | |
| "Autoencoders": { | |
| "Encoded_Features": { | |
| "Encoder_Architecture": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 64 | |
| ], | |
| "Input_Layer": 256, | |
| "Latent_Space": 32 | |
| }, | |
| "Training_Parameters": { | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01 | |
| } | |
| } | |
| }, | |
| "Fourier_Transforms": { | |
| "FFT_Coefficients": { | |
| "Amplitude": [ | |
| 0.4, | |
| 0.3, | |
| 0.2, | |
| 0.1 | |
| ], | |
| "Frequency_Bands": [ | |
| 0, | |
| 5, | |
| 10, | |
| 20 | |
| ], | |
| "Phase": [ | |
| 0.1, | |
| 0.2, | |
| 0.3, | |
| 0.4 | |
| ] | |
| } | |
| }, | |
| "Principal_Component_Analysis": { | |
| "PCA_Components": { | |
| "Explained_Variance_Ratio": [ | |
| 0.5, | |
| 0.3, | |
| 0.2 | |
| ], | |
| "Number_of_Components": 3 | |
| } | |
| }, | |
| "Wavelet_Transforms": { | |
| "Wavelet_Coefficients": { | |
| "Approximation_Coefficients": [ | |
| 0.6, | |
| 0.4 | |
| ], | |
| "Decomposition_Level": 2, | |
| "Detail_Coefficients": [ | |
| 0.2, | |
| 0.3 | |
| ], | |
| "Wavelet_Type": "db4" | |
| } | |
| } | |
| }, | |
| "Feature_Generation": { | |
| "Statistical_Features": { | |
| "Kurtosis": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Median": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Skewness": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Standard_Deviation": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| }, | |
| "Technical_Indicator_Features": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| }, | |
| "Time_Series_Features": { | |
| "Lagged_Values": { | |
| "Include_Current": true, | |
| "Lags": [ | |
| 1, | |
| 5, | |
| 10, | |
| 20 | |
| ] | |
| }, | |
| "Rolling_Window_Statistics": { | |
| "Rolling_Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Rolling_Std": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Price_Data": { | |
| "Adjustments": true, | |
| "Frequency": "1min", | |
| "Time_Frame": 60 | |
| }, | |
| "Technical_Indicators": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Simulation_Data": { | |
| "Historical_Price_Data": { | |
| "Data_Cleaning": { | |
| "Data_Normalization": { | |
| "Method": "min-max", | |
| "Parameters": [ | |
| 0, | |
| 1 | |
| ] | |
| }, | |
| "Missing_Data_Handling": { | |
| "Method": "interpolation", | |
| "Parameters": "linear" | |
| }, | |
| "Outlier_Removal": { | |
| "Method": "z-score", | |
| "Parameters": 3 | |
| } | |
| }, | |
| "Data_Sources": { | |
| "Source_1": { | |
| "Format": "csv", | |
| "Frequency": "1min", | |
| "Type": "price" | |
| }, | |
| "Source_2": { | |
| "Format": "json", | |
| "Frequency": "1day", | |
| "Type": "fundamental" | |
| } | |
| } | |
| }, | |
| "Synthetic_Data": { | |
| "Data_Generation_Methods": { | |
| "GAN": { | |
| "Architecture": { | |
| "Discriminator": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 64 | |
| ], | |
| "Input_Layer": 256, | |
| "Output_Layer": 1 | |
| }, | |
| "Generator": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 256 | |
| ], | |
| "Input_Layer": 100, | |
| "Output_Layer": 256 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01 | |
| } | |
| }, | |
| "Monte_Carlo_Simulation": { | |
| "Drift": 0.01, | |
| "Number_of_Simulations": 1000, | |
| "Time_Step": 1, | |
| "Volatility": 0.02 | |
| } | |
| } | |
| } | |
| }, | |
| "Training_Algorithm": { | |
| "A2C": { | |
| "Network_Architecture": { | |
| "Actor_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "softmax", | |
| "Number_of_Neurons": 3 | |
| } | |
| }, | |
| "Critic_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 1 | |
| } | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Discount_Factor": 0.99, | |
| "Entropy_Coefficient": 0.01, | |
| "Learning_Rate": 0.01, | |
| "Value_Loss_Coefficient": 0.5 | |
| } | |
| }, | |
| "DQN": { | |
| "Network_Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 3 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Discount_Factor": 0.95, | |
| "Exploration_Rate": 0.1, | |
| "Learning_Rate": 0.01, | |
| "Replay_Buffer_Size": 100000 | |
| } | |
| }, | |
| "PPO": { | |
| "Policy_Architecture": { | |
| "Actor_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "softmax", | |
| "Number_of_Neurons": 3 | |
| } | |
| }, | |
| "Critic_Network": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 1 | |
| } | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Clip_Range": 0.2, | |
| "Entropy_Coefficient": 0.0, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Value_Loss_Coefficient": 0.5 | |
| } | |
| } | |
| } | |
| }, | |
| "Trade_Execution": { | |
| "Signal_Generation": { | |
| "Advanced_Feature_Generation": { | |
| "Autoencoders": { | |
| "Encoded_Features": { | |
| "Encoder_Architecture": { | |
| "Hidden_Layers": [ | |
| 128, | |
| 64 | |
| ], | |
| "Input_Layer": 256, | |
| "Latent_Space": 32 | |
| }, | |
| "Training_Parameters": { | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01 | |
| } | |
| } | |
| }, | |
| "Fourier_Transforms": { | |
| "FFT_Coefficients": { | |
| "Amplitude": [ | |
| 0.4, | |
| 0.3, | |
| 0.2, | |
| 0.1 | |
| ], | |
| "Frequency_Bands": [ | |
| 0, | |
| 5, | |
| 10, | |
| 20 | |
| ], | |
| "Phase": [ | |
| 0.1, | |
| 0.2, | |
| 0.3, | |
| 0.4 | |
| ] | |
| } | |
| }, | |
| "Principal_Component_Analysis": { | |
| "PCA_Components": { | |
| "Explained_Variance_Ratio": [ | |
| 0.5, | |
| 0.3, | |
| 0.2 | |
| ], | |
| "Number_of_Components": 3 | |
| } | |
| }, | |
| "Wavelet_Transforms": { | |
| "Wavelet_Coefficients": { | |
| "Approximation_Coefficients": [ | |
| 0.6, | |
| 0.4 | |
| ], | |
| "Decomposition_Level": 2, | |
| "Detail_Coefficients": [ | |
| 0.2, | |
| 0.3 | |
| ], | |
| "Wavelet_Type": "db4" | |
| } | |
| } | |
| }, | |
| "Feature_Generation": { | |
| "Statistical_Features": { | |
| "Kurtosis": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Median": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Skewness": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Standard_Deviation": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| }, | |
| "Technical_Indicator_Features": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| }, | |
| "Time_Series_Features": { | |
| "Lagged_Values": { | |
| "Include_Current": true, | |
| "Lags": [ | |
| 1, | |
| 5, | |
| 10, | |
| 20 | |
| ] | |
| }, | |
| "Rolling_Window_Statistics": { | |
| "Rolling_Mean": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| }, | |
| "Rolling_Std": { | |
| "Calculation_Method": "mean", | |
| "Window_Size": 14 | |
| } | |
| } | |
| } | |
| }, | |
| "Machine_Learning_Models": { | |
| "GRU": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "sigmoid", | |
| "Number_of_Neurons": 1 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Optimizer": "adam" | |
| } | |
| }, | |
| "LSTM": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 64 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "tanh", | |
| "Number_of_Neurons": 32 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "sigmoid", | |
| "Number_of_Neurons": 1 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Optimizer": "adam" | |
| } | |
| }, | |
| "Neural_Networks": { | |
| "Architecture": { | |
| "Hidden_Layers": { | |
| "Layer_1": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 128 | |
| }, | |
| "Layer_2": { | |
| "Activation_Function": "relu", | |
| "Number_of_Neurons": 64 | |
| } | |
| }, | |
| "Input_Layer": { | |
| "Activation_Function": "linear", | |
| "Number_of_Neurons": 256 | |
| }, | |
| "Output_Layer": { | |
| "Activation_Function": "sigmoid", | |
| "Number_of_Neurons": 1 | |
| } | |
| }, | |
| "Training_Parameters": { | |
| "Batch_Size": 64, | |
| "Epochs": 100, | |
| "Learning_Rate": 0.01, | |
| "Optimizer": "adam" | |
| } | |
| }, | |
| "Random_Forest": { | |
| "Feature_Importance": [ | |
| 0.3, | |
| 0.2, | |
| 0.15, | |
| 0.1, | |
| 0.05 | |
| ], | |
| "Max_Depth": { | |
| "Max_Depth": 10, | |
| "Min_Depth": 2 | |
| }, | |
| "Number_of_Trees": { | |
| "Max_Trees": 500, | |
| "Min_Trees": 50 | |
| } | |
| }, | |
| "SVM": { | |
| "Kernel": { | |
| "Parameters": [ | |
| 0.1, | |
| 1, | |
| 10 | |
| ], | |
| "Type": "rbf" | |
| }, | |
| "Regularization": { | |
| "C_Value": 1.0, | |
| "Kernel_Coefficient": 0.1 | |
| } | |
| }, | |
| "XGBoost": { | |
| "Parameters": { | |
| "Colsample_Bytree": 0.8, | |
| "Gamma": 0.0, | |
| "Learning_Rate": 0.01, | |
| "Max_Depth": 6, | |
| "Min_Child_Weight": 1, | |
| "Number_of_Trees": 100, | |
| "Scale_Pos_Weight": 1, | |
| "Subsample": 0.8 | |
| } | |
| } | |
| }, | |
| "Signal_Validation": { | |
| "Backtesting": { | |
| "Historical_Data_Period": { | |
| "End_Date": "2023-01-01", | |
| "Start_Date": "2020-01-01" | |
| }, | |
| "Performance_Metrics": { | |
| "Max_Drawdown": { | |
| "Calculation_Method": "mean" | |
| }, | |
| "Return_on_Investment": { | |
| "Calculation_Method": "mean" | |
| }, | |
| "Sharpe_Ratio": { | |
| "Calculation_Method": "mean" | |
| }, | |
| "Volatility": { | |
| "Calculation_Method": "mean" | |
| } | |
| } | |
| }, | |
| "Paper_Trading": { | |
| "Execution_Speed": { | |
| "Real_Time": true, | |
| "Simulated_Time": false | |
| }, | |
| "Virtual_Capital": { | |
| "Currency": "USD", | |
| "Initial_Capital": 10000 | |
| } | |
| } | |
| }, | |
| "Technical_Indicators": { | |
| "Bollinger_Bands": { | |
| "Lower_Band": 95.0, | |
| "Middle_Band": 100.0, | |
| "Period": 14, | |
| "Standard_Deviation_Multiplier": 2, | |
| "Upper_Band": 105.0 | |
| }, | |
| "MACD": { | |
| "Fast_Period": 12, | |
| "Histogram": { | |
| "Negative": -0.3, | |
| "Positive": 0.6 | |
| }, | |
| "Signal_Line": 0.1, | |
| "Slow_Period": 26 | |
| }, | |
| "Moving_Averages": { | |
| "Exponential_Moving_Average": { | |
| "Period": 14, | |
| "Smoothing_Factor": 0.9 | |
| }, | |
| "Simple_Moving_Average": { | |
| "Calculation_Method": "mean", | |
| "Period": 14 | |
| } | |
| }, | |
| "RSI": { | |
| "Overbought_Level": 70, | |
| "Oversold_Level": 30, | |
| "Period": 14 | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } |
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