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feat: Organize notebooks and add stationarity checks

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Mohammad Aghdam
2025-10-02 00:00:16 +02:00
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README.md
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# AlphaFlow-MT5-ML-DL-Trading-Lab
## Multi-strategy MT5 research lab for ML/DL/time-series trading: data → modeling → backtests → tuning → prototype execution.
# AlphaFlow ML & DL Trading Bot Project
A comprehensive **machine learning and deep learning trading framework** that covers the entire workflow:
@@ -42,49 +41,61 @@ This project provides a flexible **template** for you to **create and add your o
## Repository Structure
```bash
# ML Bot Trading Repository Structure
# AlphaFlow ML & DL Trading Bot Repository Structure
ml_bot_trading/
AlphaFlow-MT5-ML-DL-Trading-Lab/
├── data/
│ ├── data_loader.py # MetaTrader 5 data retrieval
│ ├── data_loader.py # MetaTrader 5 data retrieval
│
├── features/
│ ├── feature_engineering.py # Technical indicators, custom features
│ ├── labeling.py # Labeling methods: next-bar, multi-bar, double-barrier, regime detection
│ ├── feature_engineering.py # Technical indicators, stationarity checks, custom features
│ ├── labeling_schemes.py # Labeling methods: next-bar, multi-bar, double-barrier, regime detection
│
├── models/
│ ├── model_training.py # Model selection, hyperparam tuning
│ ├── saved_models/ # Folder for .pkl pipelines (best_rf_pipeline.pkl, etc.)
│ ├── model_training.py # Model selection, hyperparameter tuning (Optuna, GridSearchCV)
│ ├── saved_models/ # Folder for saved model pipelines (.pkl, .joblib)
│
├── backtests/
│ ├── simple_backtest.py # Simple Pythonic backtest logic
│ ├── vectorbt_backtest.py # VectorBT-based backtesting template
│ ├── simple_backtest.py # Simple event-driven backtest logic
│ ├── vectorbt_backtest.py # VectorBT-based backtesting template
│
├── live_trading/
│ ├── regression_returns.py # Live trading script for regression returns
│ ├── multi_bar.py # Live trading script for multi-bar classification
│ ├── double_barrier.py # Live trading script for double-barrier labeling
│ ├── regime_detection.py # Live trading script for regime detection
│ ├── ... (live trading scripts)
│
├── notebooks/
│ ├── dl_notebooks/
│ │ ├── 00_eda_visualization.ipynb
│ │ ├── 01_backtests_regression_returns_dl.ipynb
│ │ ├── 01_live_trading_regression_returns_dl.ipynb
│ │ ├── 02_time_series_arima_sarima_var_lstmprice.ipynb
│ │
│ ├── eda_notebooks/
│ │ ├── 00_eda_visualization.ipynb
│ │
│ ├── ml_notebooks/
│ │ ├── 01_backtests_regression_returns.ipynb
│ │ ├── 01_live_trading_regression_returns.ipynb
│ │ ├── 02_backtests_multi_bar_classification.ipynb
│ │ ├── 02_live_trading_multi_bar_classification.ipynb
│ │ ├── 03_backtests_double_barrier_labeling.ipynb
│ │ ├── 03_live_trading_double_barrier_labeling.ipynb
│ │ ├── 04_backtests_regime_detection.ipynb
│ │ ├── 04_live_trading_regime_detection.ipynb
│ ├── exploratory/
│ │ ├── eda_visualization.ipynb
│ │ ├── integrated_pipeline_pair_trading.ipynb
│ │ └── kalman_filters_solution.ipynb
│ ├── strategies/
│ │ ├── ml/
│ │ │ ├── backtesting/
│ │ │ │ ├── regression_returns.ipynb
│ │ │ │ ├── double_barrier_labeling.ipynb
│ │ │ │ ├── multi_bar_classification.ipynb
│ │ │ │ ├── multi_bar_classification_multisymbol.ipynb
│ │ │ │ ├── multi_bar_classification_multisymbol_core_features.ipynb
│ │ │ │ ├── multi_bar_classification_multisymbol_core_features_stocks.ipynb
│ │ │ │ ├── regime_detection.ipynb
│ │ │ │ ├── momentum_strategy.ipynb
│ │ │ │ ├── pairs_trading_cointegration.ipynb
│ │ │ │ └── pairs_trading_clustering.ipynb
│ │ │ └── live_trading/
│ │ │ ├── regression_returns.ipynb
│ │ │ ├── double_barrier_labeling.ipynb
│ │ │ ├── multi_bar_classification.ipynb
│ │ │ ├── multi_bar_classification_multisymbol_core_features.ipynb
│ │ │ ├── regime_detection.ipynb
│ │ │ ├── pairs_trading_cointegration.ipynb
│ │ │ └── pairs_trading_clustering.ipynb
│ │ └── dl/
│ │ ├── backtesting/
│ │ │ ├── regression_returns.ipynb
│ │ │ └── multi_bar_classification_multisymbol.ipynb
│ │ └── live_trading/
│ │ └── regression_returns.ipynb
│ └── time_series/
│ └── arima_sarima_var_lstm.ipynb
│
├── requirements.txt
├── README.md