├── .github └── FUNDING.yml ├── .gitignore ├── Advances in Financial Machine Learning ├── Backtest Statistics │ └── Chapter14_BacktestStatistics.ipynb ├── Bet Sizing │ ├── Chapter10_Exercises (mlfinlab).ipynb │ ├── Chapter10_Exercises.ipynb │ ├── EF3M │ │ ├── __init__.py │ │ └── ef3m.py │ ├── __init__.py │ ├── ef3m_testing.ipynb │ └── readme.md ├── Cross-Validation in Finance │ └── Chapter7_Exercises_CrossValidation.ipynb ├── Ensemble Methods │ ├── Ensemble_Methods.ipynb │ ├── images │ │ ├── 100trees_to_50features.png │ │ ├── ch6_bagged_prediction.png │ │ └── relationship_small.png │ └── relational_data.csv ├── Feature Importance │ ├── Chapter8_Exercises_Feature_Importance.ipynb │ ├── Cluster_Feature_Importance.ipynb │ ├── feature_importances_mp.py │ └── img │ │ ├── MDA_feat_imp_8.1c.png │ │ ├── MDA_feat_imp_8.1c2.png │ │ ├── MDA_feat_imp_8.2a.png │ │ ├── MDA_feat_imp_8.3b.png │ │ ├── MDA_feat_imp_8.4c_10chunks.png │ │ ├── MDA_feat_imp_8.4c_1chunk.png │ │ ├── MDI_feat_imp_8.1c.png │ │ ├── MDI_feat_imp_8.1c2.png │ │ ├── MDI_feat_imp_8.2a.png │ │ ├── MDI_feat_imp_8.3b.png │ │ ├── MDI_feat_imp_8.4c_10chunks.png │ │ ├── MDI_feat_imp_8.4c_1chunk.png │ │ ├── MDI_feat_imp_8.5_1.png │ │ ├── MDI_feat_imp_8.5_1_2.png │ │ ├── MDI_feat_imp_8.5_2.png │ │ ├── MDI_feat_imp_8.5_3.png │ │ ├── MDI_feat_imp_8.5_4.png │ │ ├── MDI_feat_imp_8.5_5.png │ │ ├── SFI_feat_imp_8.1c.png │ │ ├── SFI_feat_imp_8.1c2.png │ │ ├── SFI_feat_imp_8.2a.png │ │ ├── SFI_feat_imp_8.3b.png │ │ ├── SFI_feat_imp_8.4c_10chunks.png │ │ ├── SFI_feat_imp_8.4c_1chunk.png │ │ ├── clustered_mda.png │ │ └── clustered_mdi.png ├── Financial Data Structures │ ├── Dollar-Imbalance-Bars.ipynb │ ├── ETF_trick_hedge.ipynb │ ├── Futures_Roll_Trick.ipynb │ ├── Getting Started.ipynb │ ├── Sample_Techniques.ipynb │ ├── images │ │ ├── book_implementation.png │ │ └── mlfinlab_implementation.png │ └── tutorial_data │ │ ├── ES_Trades.zip │ │ ├── dollar_bars.csv │ │ ├── tick_bars.csv │ │ ├── time_bars.csv │ │ └── volume_bars.csv ├── Fractionally Differentiated Features │ ├── Chapter5_Exercises.ipynb │ └── README.md ├── Labelling │ ├── BBand-Question.ipynb │ ├── Chapter3-Part1.ipynb │ ├── F1-Score.png │ ├── Hybrid models.png │ ├── MNIST.png │ ├── Meta-Labels-MNIST.ipynb │ ├── Model Architecture.png │ ├── README.md │ ├── Trend-Follow-Question.ipynb │ ├── readme_image.png │ └── sample_dollar_bars.csv ├── Machine Learning Asset Allocation │ ├── Chapter16.ipynb │ ├── __init__.py │ ├── cla_modified.py │ ├── hrp_modified.py │ └── mvo_modified.py ├── Microstructural Features │ ├── Chapter19-Questions.ipynb │ ├── Microstructural-Features.ipynb │ ├── __init__.py │ └── mlfinlab │ │ ├── __init__.py │ │ ├── data_structures │ │ ├── __init__.py │ │ ├── bar_feature.py │ │ ├── base_bars.py │ │ ├── imbalance_data_structures.py │ │ ├── run_data_structures.py │ │ └── standard_data_structures.py │ │ ├── features │ │ ├── __init__.py │ │ ├── fracdiff.py │ │ └── microstructural.py │ │ ├── filters │ │ ├── __init__.py │ │ └── filters.py │ │ ├── labeling │ │ ├── __init__.py │ │ └── labeling.py │ │ ├── multi_product │ │ ├── __init__.py │ │ └── etf_trick.py │ │ ├── sample_weights │ │ ├── __init__.py │ │ └── attribution.py │ │ ├── sampling │ │ ├── __init__.py │ │ ├── bootstrapping.py │ │ └── concurrent.py │ │ ├── tests │ │ ├── __init__.py │ │ ├── test_bar_feature.py │ │ ├── test_data │ │ │ ├── alloc_df.csv │ │ │ ├── close_df.csv │ │ │ ├── costs_df.csv │ │ │ ├── dollar_bar_sample.csv │ │ │ ├── imbalance_sample_data.csv │ │ │ ├── open_df.csv │ │ │ ├── rates_df.csv │ │ │ └── tick_data.csv │ │ ├── test_etf_trick.py │ │ ├── test_fast_ewma.py │ │ ├── test_filters.py │ │ ├── test_fracdiff.py │ │ ├── test_futures_roll.py │ │ ├── test_imbalance_data_structures.py │ │ ├── test_labels.py │ │ ├── test_run_data_structures.py │ │ ├── test_sample_weights.py │ │ ├── test_sampling.py │ │ └── test_standard_data_structures.py │ │ └── util │ │ ├── __init__.py │ │ ├── fast_ewma.py │ │ ├── multiprocess.py │ │ └── utils.py ├── Sample Weights │ ├── Chapter4_Exercises.ipynb │ ├── Sequential_Bootstrapping.ipynb │ └── Trend-Follow-Question-Extended-SB-Cross-Val.ipynb └── Understanding Strategy Risk │ └── Chapter15_Exercises_UnderstandingStrategyRisk.ipynb ├── Backtest Overfitting └── Backtesting.ipynb ├── Guidelines.md ├── LICENSE ├── Labelling ├── Labels Excess Over Median │ ├── excess_over_median.ipynb │ └── img │ │ └── distribution_over_median.png ├── Labels Fixed Horizon │ ├── Fixed Time Horizon.ipynb │ └── img │ │ └── fixed_horizon_labels_example.png └── Labels Tail Sets │ └── tail_set_labels_example.ipynb ├── Online Portfolio Selection ├── Data Selection.ipynb ├── Introduction to Online Portfolio Selection.ipynb ├── Online Portfolio Selection - Mean Reversion.ipynb ├── Online Portfolio Selection - Momentum.ipynb └── Online Portfolio Selection - Pattern Matching.ipynb ├── Open-Source-Soldier-of-Fortune ├── README.md ├── akwon31-submission │ ├── Submission.ipynb │ └── helper.py ├── j_gerard_submission │ ├── MAD_MIKE_HOARES_WILD_GEESE.ipynb │ └── kruskal.py ├── jihobak-submission │ ├── constituents.csv │ ├── graph.py │ ├── mst.py │ ├── selected_tickers_info.csv │ ├── sp50_1year.csv │ ├── submission_notebook.ipynb │ ├── tests │ │ ├── mst_test.py │ │ └── utils_test.py │ └── utils.py ├── masoumnia_submission │ ├── amex_rand50.csv │ ├── kruskal.py │ ├── mst_demo.ipynb │ └── tests.py └── mirca-submission │ ├── core.py │ ├── hudson-thames-skill-challenge.ipynb │ └── unittests.py ├── Portfolio Optimisation Tutorials ├── Hierarchical Clustering Asset Allocation (HCAA) │ └── HCAA Tutorial Notebook.ipynb ├── Hierarchical Risk Parity (HRP) │ └── HRP use examples.ipynb ├── Nested Clustered Optimisation (NCO) │ └── NCO.ipynb ├── Risk Estimators │ └── RiskEstimators.ipynb └── Theory Implied Correlation (TIC) │ └── TIC.ipynb ├── README.md ├── Sample-Data ├── README.md ├── classification_tree.csv ├── dollar_bars.csv ├── dollar_bars_ex_2.2.csv ├── eur_usd.csv ├── eurostoxx.csv ├── 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