mlfinlab
MlFinlab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
Adding MlFinLab to your companies pipeline is like adding a department of PhD researchers to your team.
Subpackages
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mlfinlab.backtest_statistics -
mlfinlab.bet_sizing -
mlfinlab.clustering -
mlfinlab.codependence -
mlfinlab.cross_validation -
mlfinlab.data_generation -
mlfinlab.data_structures -
mlfinlab.datasets -
mlfinlab.ensemble -
mlfinlab.feature_importance -
mlfinlab.features -
mlfinlab.filters -
mlfinlab.labeling-
mlfinlab.labeling.bull_bear -
mlfinlab.labeling.excess_over_mean -
mlfinlab.labeling.excess_over_median -
mlfinlab.labeling.fixed_time_horizon -
mlfinlab.labeling.labeling -
mlfinlab.labeling.matrix_flags -
mlfinlab.labeling.raw_return -
mlfinlab.labeling.return_vs_benchmark -
mlfinlab.labeling.tail_sets -
mlfinlab.labeling.trend_scanning
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mlfinlab.microstructural_features-
mlfinlab.microstructural_features.encoding -
mlfinlab.microstructural_features.entropy -
mlfinlab.microstructural_features.feature_generator -
mlfinlab.microstructural_features.first_generation -
mlfinlab.microstructural_features.misc -
mlfinlab.microstructural_features.second_generation -
mlfinlab.microstructural_features.third_generation
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mlfinlab.multi_product -
mlfinlab.networks -
mlfinlab.online_data_structures -
mlfinlab.regression -
mlfinlab.sample_weights -
mlfinlab.sampling -
mlfinlab.structural_breaks -
mlfinlab.util