# skfolio > Python library for portfolio optimization, factor model construction, and risk management, built on top of scikit-learn: create, fine-tune, cross-validate, and stress-test portfolio models. 2026, skfolio developers (BSD License) ## Pages - [skfolio](https://skfolio.org/index.html.md): Python library for portfolio optimization, factor model construction, and risk management, built on scikit-learn to create, fine-tune, cross-validate, and stress-test portfolio models. - [User Guide](https://skfolio.org/user_guide/index.html.md): Comprehensive user guide for skfolio: step-by-step tutorials to install, configure, and use the Python library for portfolio optimization, factor model construction, and risk management. - [Installation](https://skfolio.org/user_guide/install.html.md): `skfolio` is available on PyPI and can be installed with: - [Optimization](https://skfolio.org/user_guide/optimization.html.md): The optimization module implements a set of methods intended for portfolio optimization. - [Portfolio](https://skfolio.org/user_guide/portfolio.html.md): `Portfolio` classes implement a large set of attributes and methods intended for - [Population](https://skfolio.org/user_guide/population.html.md): A `Population` - [Prior Estimator](https://skfolio.org/user_guide/prior.html.md): A Prior Estimator in `skfolio` fits a `ReturnDistribution` - [Expected Return Estimator](https://skfolio.org/user_guide/expected_returns.html.md): An [expected return estimator](https://skfolio.org/api.html.md#mu-ref) estimates the expected return... - [Variance Estimator](https://skfolio.org/user_guide/variance.html.md): A [variance estimator](https://skfolio.org/api.html.md#variance-ref) estimates the variance vector o... - [Covariance Estimator](https://skfolio.org/user_guide/covariance.html.md): A [covariance estimator](https://skfolio.org/api.html.md#covariance-ref) estimates the covariance ma... - [Factor Models](https://skfolio.org/user_guide/factor_models.html.md): This guide covers skfolio’s factor model implementations, their API and their - [Distance Estimator](https://skfolio.org/user_guide/distance.html.md): A [distance estimator](https://skfolio.org/api.html.md#distance-ref) estimates the codependence and ... - [Clustering Estimators](https://skfolio.org/user_guide/cluster.html.md): The `skfolio.cluster` module complements `sklearn.cluster` with additional clustering - [Uncertainty Set Estimator](https://skfolio.org/user_guide/uncertainty_set.html.md): An [uncertainty set estimator](https://skfolio.org/api.html.md#uncertainty-set-ref) builds the regio... - [Pre-Selection Transformers](https://skfolio.org/user_guide/pre_selection.html.md): A [Pre-Selection transformer](https://skfolio.org/api.html.md#pre-selection-ref) performs a pre-sele... - [Cross-Sectional Transformers](https://skfolio.org/user_guide/cross_sectional_transformers.html.md): A [Cross-Sectional Transformer](https://skfolio.org/api.html.md#preprocessing-ref) normalizes each v... - [Model Selection](https://skfolio.org/user_guide/model_selection.html.md): The Model Selection module extends `sklearn.model_selection` by adding additional - [Hyper-Parameters Tuning](https://skfolio.org/user_guide/hyper_parameters_tuning.html.md): Hyper-parameters tuning in `skfolio` follows the same API as `scikit-learn`. - [Online Learning](https://skfolio.org/user_guide/online_learning.html.md): `skfolio` provides dedicated online utilities for estimators that support - [Metadata Routing](https://skfolio.org/user_guide/metadata_routing.html.md): This document shows how you can use the metadata routing mechanism to route metadata - [Datasets](https://skfolio.org/user_guide/datasets.html.md): `skfolio` comes with three native datasets available via: - [Data Preparation](https://skfolio.org/user_guide/data_preparation.html.md): Most `fit` methods of `skfolio` estimators take the assets returns as input `X`. - [Asset Data Representation](https://skfolio.org/user_guide/data_representation.html.md): The choice of data structure, data container and missing-data handling matters - [Migration Guide](https://skfolio.org/user_guide/migration.html.md): `skfolio` follows [semantic versioning](https://semver.org). The public API remains - [Examples](https://skfolio.org/auto_examples/index.html.md): Examples and tutorials for skfolio, a Python library for portfolio optimization, factor model construction, and risk management built on top of scikit-learn to create, fine-tune, cross-validate, and stress-test portfolio models. - [Mean-Risk](https://skfolio.org/auto_examples/mean_risk/index.html.md): Examples using the `MeanRisk` - [Maximum Sharpe Ratio](https://skfolio.org/auto_examples/mean_risk/plot_1_maximum_sharpe_ratio.html.md): This tutorial uses the `MeanRisk` - [Minimum CVaR](https://skfolio.org/auto_examples/mean_risk/plot_2_minimum_CVaR.html.md): This tutorial uses the `MeanRisk` - [Efficient Frontier](https://skfolio.org/auto_examples/mean_risk/plot_3_efficient_frontier.html.md): This tutorial uses the `MeanRisk` - [Mean-Variance-CDaR Surface](https://skfolio.org/auto_examples/mean_risk/plot_4_mean_variance_cdar.html.md): This tutorial uses the `MeanRisk` - [Weight Constraints](https://skfolio.org/auto_examples/mean_risk/plot_5_weight_constraints.html.md): This tutorial shows how to incorporate weight constraints into the - [Transaction Costs](https://skfolio.org/auto_examples/mean_risk/plot_6_transaction_costs.html.md): This tutorial shows how to incorporate transaction costs (TC) into the - [Management Fees](https://skfolio.org/auto_examples/mean_risk/plot_7_management_fees.html.md): This tutorial shows how to incorporate management fees (MF) into the - [L1 and L2 Regularization](https://skfolio.org/auto_examples/mean_risk/plot_8_regularization.html.md): This tutorial shows how to incorporate regularization into the - [Uncertainty Set](https://skfolio.org/auto_examples/mean_risk/plot_9_uncertainty_set.html.md): This tutorial shows how to incorporate expected returns uncertainty sets into the - [Tracking Error](https://skfolio.org/auto_examples/mean_risk/plot_10_tracking_error.html.md): This tutorial shows how to incorporate a tracking error constraint into the - [Empirical Prior](https://skfolio.org/auto_examples/mean_risk/plot_11_empirical_prior.html.md): This tutorial shows how to use the `EmpiricalPrior` - [Black & Litterman](https://skfolio.org/auto_examples/mean_risk/plot_12_black_and_litterman.html.md): This tutorial shows how to use the `BlackLitterman` - [Factor Model](https://skfolio.org/auto_examples/mean_risk/plot_13_factor_model.html.md): This tutorial shows how to use the `TimeSeriesFactorModel` - [Black & Litterman Factor Model](https://skfolio.org/auto_examples/mean_risk/plot_14_black_litterman_factor_model.html.md): This tutorial shows how to use the `TimeSeriesFactorModel` - [Cardinality Constraints](https://skfolio.org/auto_examples/mean_risk/plot_15_mip_cardinality_constraints.html.md): This tutorial shows how to use cardinality constraints with the - [Threshold Constraints](https://skfolio.org/auto_examples/mean_risk/plot_16_mip_threshold_constraints.html.md): This tutorial shows how to use threshold constraints with the - [Failure and Fallbacks](https://skfolio.org/auto_examples/mean_risk/plot_17_failure_and_fallbacks.html.md): This tutorial introduces the optimization parameters `fallback` and `raise_on_failure`. - [Factor Models](https://skfolio.org/auto_examples/factor_models/index.html.md): Examples about `CharacteristicsFactorModel` - [Characteristics Factor Model](https://skfolio.org/auto_examples/factor_models/plot_characteristics_factor_model.html.md): This tutorial shows how to build a characteristics-based cross-sectional factor - [Factor-Constrained Portfolio and Attribution](https://skfolio.org/auto_examples/factor_models/plot_factor_constrained_portfolio.html.md): This tutorial shows how to build a dollar-neutral long-short portfolio with - [Alpha Research and Factor-Neutral Portfolio](https://skfolio.org/auto_examples/factor_models/plot_alpha_factor_neutral_portfolio.html.md): This tutorial shows how to research an alpha signal that forecasts the - [Risk Budgeting](https://skfolio.org/auto_examples/risk_budgeting/index.html.md): Examples concerning the `RiskBudgeting` - [Risk Parity - Variance](https://skfolio.org/auto_examples/risk_budgeting/plot_1_risk_parity_variance.html.md): This tutorial uses the `RiskBudgeting` - [Risk Budgeting - CVaR](https://skfolio.org/auto_examples/risk_budgeting/plot_2_risk_budgeting_CVaR.html.md): This tutorial uses the `RiskBudgeting` - [Risk Parity - Covariance shrinkage](https://skfolio.org/auto_examples/risk_budgeting/plot_3_risk_parity_ledoit_wolf.html.md): This tutorial shows how to incorporate covariance shrinkage in the - [Synthetic Data & Stress Test](https://skfolio.org/auto_examples/synthetic_data/index.html.md): Examples about `SyntheticData` - [Bivariate Copulas](https://skfolio.org/auto_examples/synthetic_data/plot_1_bivariate_copulas.html.md): This tutorial introduces Bivariate Copulas estimators that are the building blocks of - [Vine Copula & Stress Test](https://skfolio.org/auto_examples/synthetic_data/plot_2_vine_copula.html.md): This tutorial presents the `VineCopula` - [Minimize CVaR on Stressed Factors](https://skfolio.org/auto_examples/synthetic_data/plot_3_min_CVaR_stressed_factors.html.md): This tutorial shows how to bridge scenario generation, factor models and portfolio - [Entropy & Opinion Pooling](https://skfolio.org/auto_examples/entropy_pooling/index.html.md): Examples about `EntropyPooling` - [Entropy Pooling](https://skfolio.org/auto_examples/entropy_pooling/plot_1_entropy_pooling.html.md): This tutorial introduces the `EntropyPooling` - [Opinion Pooling](https://skfolio.org/auto_examples/entropy_pooling/plot_2_opinion_pooling.html.md): This tutorial introduces the `OpinionPooling` - [Hierarchical Clustering and NCO](https://skfolio.org/auto_examples/clustering/index.html.md): Examples concerning hierarchical clustering based optimizations. - [Hierarchical Risk Parity - CVaR](https://skfolio.org/auto_examples/clustering/plot_1_hrp_cvar.html.md): This tutorial introduces the `HierarchicalRiskParity` - [Hierarchical Equal Risk Contribution - CDaR](https://skfolio.org/auto_examples/clustering/plot_2_herc_cdar.html.md): This tutorial introduces the - [HRP vs HERC](https://skfolio.org/auto_examples/clustering/plot_3_hrp_vs_herc.html.md): In this tutorial, we will compare the - [Nested Clusters Optimization](https://skfolio.org/auto_examples/clustering/plot_4_nco.html.md): This tutorial introduces the `NestedClustersOptimization` - [NCO - Combinatorial Purged CV](https://skfolio.org/auto_examples/clustering/plot_5_nco_grid_search.html.md): The previous tutorial introduced the - [Schur Complementary Allocation](https://skfolio.org/auto_examples/clustering/plot_6_schur.html.md): This tutorial introduces the `SchurComplementary` - [Maximum Diversification](https://skfolio.org/auto_examples/maximum_diversification/index.html.md): Examples concerning the `MaximumDiversification` - [Maximum Diversification](https://skfolio.org/auto_examples/maximum_diversification/plot_1_maximum_diversification.html.md): This tutorial uses the `MaximumDiversification` - [Distributionally Robust CVaR](https://skfolio.org/auto_examples/distributionally_robust_cvar/index.html.md): Examples concerning the `DistributionallyRobustCVaR` - [Distributionally Robust CVaR](https://skfolio.org/auto_examples/distributionally_robust_cvar/plot_1_distributionally_robust_cvar.html.md): This tutorial introduces the `DistributionallyRobustCVaR` - [Ensemble Optimizations](https://skfolio.org/auto_examples/ensemble/index.html.md): Examples concerning ensemble optimizations. - [Stacking Optimization](https://skfolio.org/auto_examples/ensemble/plot_1_stacking.html.md): This tutorial introduces the `StackingOptimization` - [Model Selection](https://skfolio.org/auto_examples/model_selection/index.html.md): Model selection is an integral part of portfolio construction and therefore appears in - [Multiple Randomized Cross-Validation](https://skfolio.org/auto_examples/model_selection/plot_1_multiple_randomized_cv.html.md): This tutorial introduces `MultipleRandomizedCV` - [Online Learning](https://skfolio.org/auto_examples/online_learning/index.html.md): Examples demonstrating online covariance evaluation, online hyperparameter - [Online Covariance Forecast Evaluation](https://skfolio.org/auto_examples/online_learning/plot_1_online_covariance_forecast_evaluation.html.md): This tutorial shows how to evaluate online covariance estimators with - [Online Covariance Hyperparameter Tuning](https://skfolio.org/auto_examples/online_learning/plot_2_online_hyperparameter_tuning.html.md): This tutorial shows how to tune covariance estimator hyperparameters in an online - [Online Evaluation of Portfolio Optimization](https://skfolio.org/auto_examples/online_learning/plot_3_online_portfolio_optimization_evaluation.html.md): This tutorial shows how to tune a `MeanRisk` - [Pre-selection](https://skfolio.org/auto_examples/pre_selection/index.html.md): Examples of using pre-selection transformers - [Drop Highly Correlated Assets](https://skfolio.org/auto_examples/pre_selection/plot_1_drop_correlated.html.md): This tutorial introduces the pre-selection transformers - [Select Best Performers](https://skfolio.org/auto_examples/pre_selection/plot_2_select_best_performers.html.md): This tutorial introduces the pre-selection transformers - [Custom Pre-selection Using Volumes](https://skfolio.org/auto_examples/pre_selection/plot_3_custom_pre_selection_volumes.html.md): This tutorial demonstrates how to implement a custom pre-selection transformer - [Handling Incomplete Datasets: Inception, Expiry, and Default](https://skfolio.org/auto_examples/pre_selection/plot_4_incomplete_dataset.html.md): When working with large datasets over long timeframes, we commonly encounter: - [Metadata Routing](https://skfolio.org/auto_examples/metadata_routing/index.html.md): Examples about metadata routing. - [Using Implied Volatility with Metadata Routing](https://skfolio.org/auto_examples/metadata_routing/plot_1_implied_volatility.html.md): This tutorial shows how to use metadata routing - [Data Preparation](https://skfolio.org/auto_examples/data_preparation/index.html.md): Examples about data preparation. - [Investment Horizon](https://skfolio.org/auto_examples/data_preparation/plot_1_investment_horizon.html.md): This tutorial explores the difference between the general - [API Reference](https://skfolio.org/api.html.md): API reference for skfolio: detailed documentation of functions, classes, and modules for portfolio optimization, factor model construction, and risk management in Python. - [skfolio.measures.BaseMeasure](https://skfolio.org/generated/skfolio.measures.BaseMeasure.html.md): Base Enum of measures. - [skfolio.measures.PerfMeasure](https://skfolio.org/generated/skfolio.measures.PerfMeasure.html.md): Enumeration of performance measures. - [skfolio.measures.RiskMeasure](https://skfolio.org/generated/skfolio.measures.RiskMeasure.html.md): Enumeration of risk measures. - [skfolio.measures.ExtraRiskMeasure](https://skfolio.org/generated/skfolio.measures.ExtraRiskMeasure.html.md): Enumeration of other risk measures not used in convex optimization. - [skfolio.measures.RatioMeasure](https://skfolio.org/generated/skfolio.measures.RatioMeasure.html.md): Enumeration of ratio measures. - [skfolio.measures.mean](https://skfolio.org/generated/skfolio.measures.mean.html.md): Compute the mean. - [skfolio.measures.get_cumulative_returns](https://skfolio.org/generated/skfolio.measures.get_cumulative_returns.html.md): Compute the cumulative returns from a series of returns. - [skfolio.measures.get_drawdowns](https://skfolio.org/generated/skfolio.measures.get_drawdowns.html.md): Compute the drawdowns’ series from the returns. - [skfolio.measures.variance](https://skfolio.org/generated/skfolio.measures.variance.html.md): Compute the variance (second moment). - [skfolio.measures.semi_variance](https://skfolio.org/generated/skfolio.measures.semi_variance.html.md): Compute the semi-variance (second lower partial moment). - [skfolio.measures.standard_deviation](https://skfolio.org/generated/skfolio.measures.standard_deviation.html.md): Compute the standard-deviation (square root of the second moment). - [skfolio.measures.semi_deviation](https://skfolio.org/generated/skfolio.measures.semi_deviation.html.md): Compute the semi-deviation (square root of the second lower partial moment). - [skfolio.measures.third_central_moment](https://skfolio.org/generated/skfolio.measures.third_central_moment.html.md): Compute the third central moment. - [skfolio.measures.fourth_central_moment](https://skfolio.org/generated/skfolio.measures.fourth_central_moment.html.md): Compute the Fourth central moment. - [skfolio.measures.fourth_lower_partial_moment](https://skfolio.org/generated/skfolio.measures.fourth_lower_partial_moment.html.md): Compute the fourth lower partial moment. - [skfolio.measures.skew](https://skfolio.org/generated/skfolio.measures.skew.html.md): Compute the Skew. - [skfolio.measures.kurtosis](https://skfolio.org/generated/skfolio.measures.kurtosis.html.md): Compute the Kurtosis. - [skfolio.measures.cvar](https://skfolio.org/generated/skfolio.measures.cvar.html.md): Compute the historical CVaR (conditional value at risk). - [skfolio.measures.mean_absolute_deviation](https://skfolio.org/generated/skfolio.measures.mean_absolute_deviation.html.md): Compute the mean absolute deviation (MAD). - [skfolio.measures.value_at_risk](https://skfolio.org/generated/skfolio.measures.value_at_risk.html.md): Compute the historical value at risk (VaR). - [skfolio.measures.worst_realization](https://skfolio.org/generated/skfolio.measures.worst_realization.html.md): Compute the worst realization (worst return). - [skfolio.measures.first_lower_partial_moment](https://skfolio.org/generated/skfolio.measures.first_lower_partial_moment.html.md): Compute the first lower partial moment. - [skfolio.measures.entropic_risk_measure](https://skfolio.org/generated/skfolio.measures.entropic_risk_measure.html.md): Compute the entropic risk measure. - [skfolio.measures.evar](https://skfolio.org/generated/skfolio.measures.evar.html.md): Compute the EVaR (entropic value at risk) and its associated risk aversion. - [skfolio.measures.drawdown_at_risk](https://skfolio.org/generated/skfolio.measures.drawdown_at_risk.html.md): Compute the Drawdown at risk. - [skfolio.measures.cdar](https://skfolio.org/generated/skfolio.measures.cdar.html.md): Compute the historical CDaR (conditional drawdown at risk). - [skfolio.measures.max_drawdown](https://skfolio.org/generated/skfolio.measures.max_drawdown.html.md): Compute the maximum drawdown. - [skfolio.measures.average_drawdown](https://skfolio.org/generated/skfolio.measures.average_drawdown.html.md): Compute the average drawdown. - [skfolio.measures.edar](https://skfolio.org/generated/skfolio.measures.edar.html.md): Compute the EDaR (entropic drawdown at risk). - [skfolio.measures.ulcer_index](https://skfolio.org/generated/skfolio.measures.ulcer_index.html.md): Compute the Ulcer index. - [skfolio.measures.gini_mean_difference](https://skfolio.org/generated/skfolio.measures.gini_mean_difference.html.md): Compute the Gini mean difference (GMD). - [skfolio.measures.owa_gmd_weights](https://skfolio.org/generated/skfolio.measures.owa_gmd_weights.html.md): Compute the OWA weights used for the Gini mean difference (GMD) computation. - [skfolio.measures.effective_number_assets](https://skfolio.org/generated/skfolio.measures.effective_number_assets.html.md): Compute the effective number of assets, defined as the inverse of the - [skfolio.measures.correlation](https://skfolio.org/generated/skfolio.measures.correlation.html.md): Compute the correlation matrix. - [skfolio.portfolio.BasePortfolio](https://skfolio.org/generated/skfolio.portfolio.BasePortfolio.html.md): Base Portfolio class for all portfolios in skfolio. - [skfolio.portfolio.Portfolio](https://skfolio.org/generated/skfolio.portfolio.Portfolio.html.md): Portfolio class. - [skfolio.portfolio.FailedPortfolio](https://skfolio.org/generated/skfolio.portfolio.FailedPortfolio.html.md): Portfolio object returned when an optimization step fails. It acts as a sentinel - [skfolio.portfolio.MultiPeriodPortfolio](https://skfolio.org/generated/skfolio.portfolio.MultiPeriodPortfolio.html.md): Multi-Period Portfolio class. - [skfolio.population.Population](https://skfolio.org/generated/skfolio.population.Population.html.md): Population Class. - [skfolio.containers.AssetPanel](https://skfolio.org/generated/skfolio.containers.AssetPanel.html.md): Container for aligned cross-sectional asset data. - [skfolio.containers.AssetPanelView](https://skfolio.org/generated/skfolio.containers.AssetPanelView.html.md): Observation-sliced view into an `AssetPanel`. - [skfolio.containers.BaseField](https://skfolio.org/generated/skfolio.containers.BaseField.html.md): Base class for fields stored in an `AssetPanel`. - [skfolio.containers.Field2D](https://skfolio.org/generated/skfolio.containers.Field2D.html.md): Numeric 2D field with axes (observations, assets). - [skfolio.containers.Field3D](https://skfolio.org/generated/skfolio.containers.Field3D.html.md): Numeric 3D field with axes (observations, assets, third_axis). - [skfolio.containers.FieldCategorical](https://skfolio.org/generated/skfolio.containers.FieldCategorical.html.md): Integer-coded categorical 2D field. - [skfolio.containers.InactivePolicy](https://skfolio.org/generated/skfolio.containers.InactivePolicy.html.md): Validation policy for values outside an `AssetPanel` active universe. - [skfolio.containers.concat](https://skfolio.org/generated/skfolio.containers.concat.html.md): Concatenate panels along the observation axis. - [skfolio.base.BaseAssetPanelTransformer](https://skfolio.org/generated/skfolio.base.BaseAssetPanelTransformer.html.md): Base class for estimators that transform asset panel data. - [skfolio.base.BaseComposition](https://skfolio.org/generated/skfolio.base.BaseComposition.html.md): Handles parameter management for ensemble estimators. - [skfolio.optimization.BaseOptimization](https://skfolio.org/generated/skfolio.optimization.BaseOptimization.html.md): Base class for all portfolio optimizations in skfolio. - [skfolio.optimization.EqualWeighted](https://skfolio.org/generated/skfolio.optimization.EqualWeighted.html.md): Equally Weighted estimator. - [skfolio.optimization.InverseVolatility](https://skfolio.org/generated/skfolio.optimization.InverseVolatility.html.md): Inverse Volatility estimator. - [skfolio.optimization.Random](https://skfolio.org/generated/skfolio.optimization.Random.html.md): Random weight estimator. - [skfolio.optimization.ObjectiveFunction](https://skfolio.org/generated/skfolio.optimization.ObjectiveFunction.html.md): Enumeration of objective functions. - [skfolio.optimization.ConvexOptimization](https://skfolio.org/generated/skfolio.optimization.ConvexOptimization.html.md): Base class for all convex optimization estimators in skfolio. - [skfolio.optimization.MeanRisk](https://skfolio.org/generated/skfolio.optimization.MeanRisk.html.md): Mean-Risk Optimization estimator. - [skfolio.optimization.BenchmarkTracker](https://skfolio.org/generated/skfolio.optimization.BenchmarkTracker.html.md): Benchmark Tracker Optimization estimator. - [skfolio.optimization.RiskBudgeting](https://skfolio.org/generated/skfolio.optimization.RiskBudgeting.html.md): Risk Budgeting Optimization estimator. - [skfolio.optimization.MaximumDiversification](https://skfolio.org/generated/skfolio.optimization.MaximumDiversification.html.md): Maximum Diversification Optimization estimator. - [skfolio.optimization.DistributionallyRobustCVaR](https://skfolio.org/generated/skfolio.optimization.DistributionallyRobustCVaR.html.md): Distributionally Robust CVaR. - [skfolio.optimization.BaseHierarchicalOptimization](https://skfolio.org/generated/skfolio.optimization.BaseHierarchicalOptimization.html.md): Base Hierarchical Clustering Optimization estimator. - [skfolio.optimization.HierarchicalRiskParity](https://skfolio.org/generated/skfolio.optimization.HierarchicalRiskParity.html.md): Hierarchical Risk Parity estimator. - [skfolio.optimization.HierarchicalEqualRiskContribution](https://skfolio.org/generated/skfolio.optimization.HierarchicalEqualRiskContribution.html.md): Hierarchical Equal Risk Contribution estimator. - [skfolio.optimization.SchurComplementary](https://skfolio.org/generated/skfolio.optimization.SchurComplementary.html.md): Schur Complementary Allocation estimator. - [skfolio.optimization.NestedClustersOptimization](https://skfolio.org/generated/skfolio.optimization.NestedClustersOptimization.html.md): Nested Clusters Optimization estimator. - [skfolio.optimization.StackingOptimization](https://skfolio.org/generated/skfolio.optimization.StackingOptimization.html.md): Stack of optimizations with a final optimization. - [skfolio.prior.ReturnDistribution](https://skfolio.org/generated/skfolio.prior.ReturnDistribution.html.md): Return distribution estimated by a prior estimator. - [skfolio.prior.FactorModel](https://skfolio.org/generated/skfolio.prior.FactorModel.html.md): Factor model decomposition of asset returns. - [skfolio.prior.CovarianceSqrt](https://skfolio.org/generated/skfolio.prior.CovarianceSqrt.html.md): Matrix square root decomposition of a covariance matrix. - [skfolio.prior.BasePrior](https://skfolio.org/generated/skfolio.prior.BasePrior.html.md): Base class for all prior estimators in skfolio. - [skfolio.prior.EmpiricalPrior](https://skfolio.org/generated/skfolio.prior.EmpiricalPrior.html.md): Empirical Prior estimator. - [skfolio.prior.BlackLitterman](https://skfolio.org/generated/skfolio.prior.BlackLitterman.html.md): Black & Litterman estimator. - [skfolio.prior.TimeSeriesFactorModel](https://skfolio.org/generated/skfolio.prior.TimeSeriesFactorModel.html.md): Time-series factor model estimator. - [skfolio.prior.CharacteristicsFactorModel](https://skfolio.org/generated/skfolio.prior.CharacteristicsFactorModel.html.md): Characteristics-based cross-sectional factor model. - [skfolio.prior.SyntheticData](https://skfolio.org/generated/skfolio.prior.SyntheticData.html.md): Synthetic Data Estimator. - [skfolio.prior.EntropyPooling](https://skfolio.org/generated/skfolio.prior.EntropyPooling.html.md): Entropy Pooling estimator. - [skfolio.prior.OpinionPooling](https://skfolio.org/generated/skfolio.prior.OpinionPooling.html.md): Opinion Pooling estimator. - [skfolio.prior.BaseLoadingMatrix](https://skfolio.org/generated/skfolio.prior.BaseLoadingMatrix.html.md): Base class for all Loading Matrix estimators. - [skfolio.prior.LoadingMatrixRegression](https://skfolio.org/generated/skfolio.prior.LoadingMatrixRegression.html.md): Loading Matrix Regression estimator. - [skfolio.descriptor.BaseDescriptor](https://skfolio.org/generated/skfolio.descriptor.BaseDescriptor.html.md): Base class for all descriptor transformers. - [skfolio.descriptor.AccrualsCashFlow](https://skfolio.org/generated/skfolio.descriptor.AccrualsCashFlow.html.md): Cash-flow statement accruals descriptor. - [skfolio.descriptor.AnalystDispersionToPrice](https://skfolio.org/generated/skfolio.descriptor.AnalystDispersionToPrice.html.md): Analyst forecast dispersion to price descriptor. - [skfolio.descriptor.AssetTurnover](https://skfolio.org/generated/skfolio.descriptor.AssetTurnover.html.md): Asset turnover descriptor. - [skfolio.descriptor.AssetsGrowthRate](https://skfolio.org/generated/skfolio.descriptor.AssetsGrowthRate.html.md): Asset growth rate descriptor. - [skfolio.descriptor.BookLeverage](https://skfolio.org/generated/skfolio.descriptor.BookLeverage.html.md): Book leverage descriptor. - [skfolio.descriptor.BookToPrice](https://skfolio.org/generated/skfolio.descriptor.BookToPrice.html.md): Book-to-price ratio descriptor. - [skfolio.descriptor.CapexToAssetsChangeInIntensity](https://skfolio.org/generated/skfolio.descriptor.CapexToAssetsChangeInIntensity.html.md): Lagged change in capex-to-assets intensity. - [skfolio.descriptor.CashFlowToAssets](https://skfolio.org/generated/skfolio.descriptor.CashFlowToAssets.html.md): Cash flow to assets descriptor. - [skfolio.descriptor.CashFlowToPrice](https://skfolio.org/generated/skfolio.descriptor.CashFlowToPrice.html.md): Cash-flow-to-price ratio descriptor. - [skfolio.descriptor.ChangeInIntensity](https://skfolio.org/generated/skfolio.descriptor.ChangeInIntensity.html.md): Lagged change in a field-to-scale ratio. - [skfolio.descriptor.ChangeToScale](https://skfolio.org/generated/skfolio.descriptor.ChangeToScale.html.md): Lagged change normalized by a positive scale. - [skfolio.descriptor.DaysToCover](https://skfolio.org/generated/skfolio.descriptor.DaysToCover.html.md): Exponentially weighted days-to-cover descriptor. - [skfolio.descriptor.DebtToAssets](https://skfolio.org/generated/skfolio.descriptor.DebtToAssets.html.md): Debt-to-assets ratio descriptor. - [skfolio.descriptor.DividendToPrice](https://skfolio.org/generated/skfolio.descriptor.DividendToPrice.html.md): Dividend-to-price ratio descriptor. - [skfolio.descriptor.EWAmihudIlliquidity](https://skfolio.org/generated/skfolio.descriptor.EWAmihudIlliquidity.html.md): Exponentially weighted Amihud illiquidity descriptor. - [skfolio.descriptor.EWDownsideBeta](https://skfolio.org/generated/skfolio.descriptor.EWDownsideBeta.html.md): Exponentially weighted downside beta descriptor. - [skfolio.descriptor.EWDownsideVolatility](https://skfolio.org/generated/skfolio.descriptor.EWDownsideVolatility.html.md): Exponentially weighted downside return volatility descriptor. - [skfolio.descriptor.EWMacroSensitivity](https://skfolio.org/generated/skfolio.descriptor.EWMacroSensitivity.html.md): EWMA macro sensitivity after removing market exposure. - [skfolio.descriptor.EWMarketBeta](https://skfolio.org/generated/skfolio.descriptor.EWMarketBeta.html.md): Exponentially weighted market beta descriptor. - [skfolio.descriptor.EWMomentum](https://skfolio.org/generated/skfolio.descriptor.EWMomentum.html.md): Exponentially weighted momentum descriptor. - [skfolio.descriptor.EWResidualDownsideVolatility](https://skfolio.org/generated/skfolio.descriptor.EWResidualDownsideVolatility.html.md): Exponentially weighted downside CAPM residual volatility descriptor. - [skfolio.descriptor.EWResidualVolatility](https://skfolio.org/generated/skfolio.descriptor.EWResidualVolatility.html.md): Exponentially weighted CAPM residual volatility descriptor. - [skfolio.descriptor.EWShareTurnover](https://skfolio.org/generated/skfolio.descriptor.EWShareTurnover.html.md): Exponentially weighted share turnover descriptor. - [skfolio.descriptor.EWVolatility](https://skfolio.org/generated/skfolio.descriptor.EWVolatility.html.md): Exponentially weighted volatility descriptor. - [skfolio.descriptor.EarningsChangeToPrice](https://skfolio.org/generated/skfolio.descriptor.EarningsChangeToPrice.html.md): Lagged earnings change divided by current market capitalization. - [skfolio.descriptor.EarningsToPrice](https://skfolio.org/generated/skfolio.descriptor.EarningsToPrice.html.md): Earnings-to-price ratio descriptor. - [skfolio.descriptor.EbitdaToEnterpriseValue](https://skfolio.org/generated/skfolio.descriptor.EbitdaToEnterpriseValue.html.md): EBITDA-to-enterprise-value ratio descriptor. - [skfolio.descriptor.ForwardDividendToPrice](https://skfolio.org/generated/skfolio.descriptor.ForwardDividendToPrice.html.md): Forward dividend-to-price ratio descriptor. - [skfolio.descriptor.ForwardEarningsToPrice](https://skfolio.org/generated/skfolio.descriptor.ForwardEarningsToPrice.html.md): Forward earnings-to-price ratio descriptor. - [skfolio.descriptor.GrossMargin](https://skfolio.org/generated/skfolio.descriptor.GrossMargin.html.md): Gross margin descriptor. - [skfolio.descriptor.GrossProfitability](https://skfolio.org/generated/skfolio.descriptor.GrossProfitability.html.md): Gross profitability descriptor. - [skfolio.descriptor.GrowthRate](https://skfolio.org/generated/skfolio.descriptor.GrowthRate.html.md): Period-over-period growth rate descriptor. - [skfolio.descriptor.IssuanceGrowthRate](https://skfolio.org/generated/skfolio.descriptor.IssuanceGrowthRate.html.md): Issuance growth rate descriptor. - [skfolio.descriptor.LogMarketCap](https://skfolio.org/generated/skfolio.descriptor.LogMarketCap.html.md): Log market capitalization descriptor. - [skfolio.descriptor.MarketLeverage](https://skfolio.org/generated/skfolio.descriptor.MarketLeverage.html.md): Market leverage descriptor. - [skfolio.descriptor.MaxReturn](https://skfolio.org/generated/skfolio.descriptor.MaxReturn.html.md): Maximum return over a trailing window. - [skfolio.descriptor.Passthrough](https://skfolio.org/generated/skfolio.descriptor.Passthrough.html.md): Passthrough descriptor for an `AssetPanel` - [skfolio.descriptor.ReturnOnAssets](https://skfolio.org/generated/skfolio.descriptor.ReturnOnAssets.html.md): Return on assets (ROA) descriptor. - [skfolio.descriptor.ReturnOnEquity](https://skfolio.org/generated/skfolio.descriptor.ReturnOnEquity.html.md): Return on equity (ROE) descriptor. - [skfolio.descriptor.Reversal](https://skfolio.org/generated/skfolio.descriptor.Reversal.html.md): Fixed-window short-term reversal descriptor. - [skfolio.descriptor.RollingMomentum](https://skfolio.org/generated/skfolio.descriptor.RollingMomentum.html.md): Fixed-window momentum descriptor. - [skfolio.descriptor.SalesGrowthRate](https://skfolio.org/generated/skfolio.descriptor.SalesGrowthRate.html.md): Sales growth rate descriptor. - [skfolio.descriptor.SalesToEnterpriseValue](https://skfolio.org/generated/skfolio.descriptor.SalesToEnterpriseValue.html.md): Sales to enterprise value descriptor. - [skfolio.descriptor.SalesToPrice](https://skfolio.org/generated/skfolio.descriptor.SalesToPrice.html.md): Sales-to-price ratio descriptor. - [skfolio.descriptor.ShareholderYield](https://skfolio.org/generated/skfolio.descriptor.ShareholderYield.html.md): Shareholder yield descriptor. - [skfolio.descriptor.ShortInterest](https://skfolio.org/generated/skfolio.descriptor.ShortInterest.html.md): Short interest descriptor. - [skfolio.factor_exposure.BaseFactorExposure](https://skfolio.org/generated/skfolio.factor_exposure.BaseFactorExposure.html.md): Base class for factor exposure estimators. - [skfolio.factor_exposure.DerivedFactor](https://skfolio.org/generated/skfolio.factor_exposure.DerivedFactor.html.md): Factor exposure derived from another factor’s computed exposure. - [skfolio.factor_exposure.FixedWeightedFactor](https://skfolio.org/generated/skfolio.factor_exposure.FixedWeightedFactor.html.md): Factor exposure as a fixed weighted combination of descriptors. - [skfolio.factor_exposure.GlobalFactor](https://skfolio.org/generated/skfolio.factor_exposure.GlobalFactor.html.md): Constant factor exposure equal to one for every asset. - [skfolio.factor_exposure.OneHotCategoricalFactors](https://skfolio.org/generated/skfolio.factor_exposure.OneHotCategoricalFactors.html.md): One-hot factor exposures from a categorical field. - [skfolio.alpha.BaseAlpha](https://skfolio.org/generated/skfolio.alpha.BaseAlpha.html.md): Base class for all Alpha estimators in skfolio. - [skfolio.alpha.EWSharpeOptimalAlpha](https://skfolio.org/generated/skfolio.alpha.EWSharpeOptimalAlpha.html.md): Exponentially weighted least-squares Sharpe-optimal alpha estimator. - [skfolio.alpha.FixedWeightedAlpha](https://skfolio.org/generated/skfolio.alpha.FixedWeightedAlpha.html.md): Fixed-weighted descriptor alpha estimator. - [skfolio.alpha.PredictorAlpha](https://skfolio.org/generated/skfolio.alpha.PredictorAlpha.html.md): Predictor alpha estimator using a user-provided regressor. - [skfolio.alpha.AlphaForecastComparison](https://skfolio.org/generated/skfolio.alpha.AlphaForecastComparison.html.md): Side-by-side comparison of alpha forecast evaluations. - [skfolio.alpha.AlphaForecastEvaluation](https://skfolio.org/generated/skfolio.alpha.AlphaForecastEvaluation.html.md): Out-of-sample alpha forecast evaluation. - [skfolio.alpha.alpha_forecast_evaluation](https://skfolio.org/generated/skfolio.alpha.alpha_forecast_evaluation.html.md): Evaluate alpha forecast quality. - [skfolio.alpha.ForecastUnit](https://skfolio.org/generated/skfolio.alpha.ForecastUnit.html.md): Unit of the intermediate alpha forecast. - [skfolio.utils.stats.CSWeighting](https://skfolio.org/generated/skfolio.utils.stats.CSWeighting.html.md): Cross-sectional weighting. - [skfolio.utils.stats.CorrelationMethod](https://skfolio.org/generated/skfolio.utils.stats.CorrelationMethod.html.md): Correlation method. - [skfolio.attribution.Attribution](https://skfolio.org/generated/skfolio.attribution.Attribution.html.md): Factor attribution result. - [skfolio.attribution.AssetBreakdown](https://skfolio.org/generated/skfolio.attribution.AssetBreakdown.html.md): Per-asset attribution breakdown. - [skfolio.attribution.AssetByFactorContribution](https://skfolio.org/generated/skfolio.attribution.AssetByFactorContribution.html.md): Asset-by-factor contribution breakdown. - [skfolio.attribution.BaseBreakdown](https://skfolio.org/generated/skfolio.attribution.BaseBreakdown.html.md): Base class for attribution breakdowns. - [skfolio.attribution.Component](https://skfolio.org/generated/skfolio.attribution.Component.html.md): Portfolio attribution component. - [skfolio.attribution.FactorBreakdown](https://skfolio.org/generated/skfolio.attribution.FactorBreakdown.html.md): Per-factor attribution breakdown. - [skfolio.attribution.FamilyBreakdown](https://skfolio.org/generated/skfolio.attribution.FamilyBreakdown.html.md): Family-level attribution breakdown. - [skfolio.attribution.predicted_factor_attribution](https://skfolio.org/generated/skfolio.attribution.predicted_factor_attribution.html.md): Compute predicted (ex-ante) factor volatility and return attribution. - [skfolio.attribution.realized_factor_attribution](https://skfolio.org/generated/skfolio.attribution.realized_factor_attribution.html.md): Compute realized (ex-post) factor volatility and return attribution. - [skfolio.attribution.rolling_realized_factor_attribution](https://skfolio.org/generated/skfolio.attribution.rolling_realized_factor_attribution.html.md): Compute rolling realized (ex-post) factor volatility and return attribution. - [skfolio.moments.BaseMu](https://skfolio.org/generated/skfolio.moments.BaseMu.html.md): Base class for all expected returns estimators in skfolio. - [skfolio.moments.EmpiricalMu](https://skfolio.org/generated/skfolio.moments.EmpiricalMu.html.md): Empirical Expected Returns (Mu) estimator. - [skfolio.moments.EWMu](https://skfolio.org/generated/skfolio.moments.EWMu.html.md): Exponentially Weighted Expected Returns (Mu) estimator. - [skfolio.moments.ShrunkMu](https://skfolio.org/generated/skfolio.moments.ShrunkMu.html.md): Shrinkage Expected Returns (Mu) estimator. - [skfolio.moments.EquilibriumMu](https://skfolio.org/generated/skfolio.moments.EquilibriumMu.html.md): Equilibrium Expected Returns (Mu) estimator. - [skfolio.moments.ShrunkMuMethods](https://skfolio.org/generated/skfolio.moments.ShrunkMuMethods.html.md): Shrinkage methods for the ShrunkMu estimator. - [skfolio.moments.BaseVariance](https://skfolio.org/generated/skfolio.moments.BaseVariance.html.md): Base class for all variance estimators in `skfolio`. - [skfolio.moments.EmpiricalVariance](https://skfolio.org/generated/skfolio.moments.EmpiricalVariance.html.md): Empirical Variance estimator. - [skfolio.moments.EWVariance](https://skfolio.org/generated/skfolio.moments.EWVariance.html.md): Exponentially Weighted Variance estimator. - [skfolio.moments.RegimeAdjustedEWVariance](https://skfolio.org/generated/skfolio.moments.RegimeAdjustedEWVariance.html.md): Exponentially weighted variance estimator with regime adjustment via the - [skfolio.moments.BaseCovariance](https://skfolio.org/generated/skfolio.moments.BaseCovariance.html.md): Base class for all covariance estimators in `skfolio`. - [skfolio.moments.RegimeAdjustmentMethod](https://skfolio.org/generated/skfolio.moments.RegimeAdjustmentMethod.html.md): Transformation used to map the STVU statistic to the volatility multiplier. - [skfolio.moments.RegimeAdjustmentTarget](https://skfolio.org/generated/skfolio.moments.RegimeAdjustmentTarget.html.md): Target dimension used to calibrate the short-term volatility update (STVU). - [skfolio.moments.EmpiricalCovariance](https://skfolio.org/generated/skfolio.moments.EmpiricalCovariance.html.md): Empirical Covariance estimator. - [skfolio.moments.EWCovariance](https://skfolio.org/generated/skfolio.moments.EWCovariance.html.md): Exponentially Weighted Covariance estimator with NaN-aware pairwise updates. - [skfolio.moments.GerberCovariance](https://skfolio.org/generated/skfolio.moments.GerberCovariance.html.md): Gerber Covariance estimator. - [skfolio.moments.DenoiseCovariance](https://skfolio.org/generated/skfolio.moments.DenoiseCovariance.html.md): Covariance Denoising estimator. - [skfolio.moments.DetoneCovariance](https://skfolio.org/generated/skfolio.moments.DetoneCovariance.html.md): Covariance Detoning estimator. - [skfolio.moments.LedoitWolf](https://skfolio.org/generated/skfolio.moments.LedoitWolf.html.md): LedoitWolf Covariance Estimator. - [skfolio.moments.OAS](https://skfolio.org/generated/skfolio.moments.OAS.html.md): Oracle Approximating Shrinkage Estimator as proposed in [[1]](#re9a22b087643-1). - [skfolio.moments.ShrunkCovariance](https://skfolio.org/generated/skfolio.moments.ShrunkCovariance.html.md): Covariance estimator with shrinkage. - [skfolio.moments.GraphicalLassoCV](https://skfolio.org/generated/skfolio.moments.GraphicalLassoCV.html.md): Sparse inverse covariance with cross-validated choice of the l1 penalty. - [skfolio.moments.ImpliedCovariance](https://skfolio.org/generated/skfolio.moments.ImpliedCovariance.html.md): Implied Covariance estimator. - [skfolio.moments.RegimeAdjustedEWCovariance](https://skfolio.org/generated/skfolio.moments.RegimeAdjustedEWCovariance.html.md): Exponentially weighted covariance estimator with regime adjustment via the - [skfolio.distance.BaseDistance](https://skfolio.org/generated/skfolio.distance.BaseDistance.html.md): Base class for all distance estimators in skfolio. - [skfolio.distance.PearsonDistance](https://skfolio.org/generated/skfolio.distance.PearsonDistance.html.md): Pearson Distance estimator. - [skfolio.distance.KendallDistance](https://skfolio.org/generated/skfolio.distance.KendallDistance.html.md): Kendall Distance estimator. - [skfolio.distance.SpearmanDistance](https://skfolio.org/generated/skfolio.distance.SpearmanDistance.html.md): Spearman Distance estimator. - [skfolio.distance.CovarianceDistance](https://skfolio.org/generated/skfolio.distance.CovarianceDistance.html.md): Covariance Distance estimator. - [skfolio.distance.DistanceCorrelation](https://skfolio.org/generated/skfolio.distance.DistanceCorrelation.html.md): Distance Correlation estimator. - [skfolio.distance.MutualInformation](https://skfolio.org/generated/skfolio.distance.MutualInformation.html.md): Mutual Information estimator. - [skfolio.cluster.HierarchicalClustering](https://skfolio.org/generated/skfolio.cluster.HierarchicalClustering.html.md): Hierarchical Clustering. - [skfolio.cluster.LinkageMethod](https://skfolio.org/generated/skfolio.cluster.LinkageMethod.html.md): Methods for calculating the distance between clusters in the linkage matrix. - [skfolio.uncertainty_set.UncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.UncertaintySet.html.md): Norm-ball uncertainty set. - [skfolio.uncertainty_set.CompactCovarianceUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.CompactCovarianceUncertaintySet.html.md): Compact representation of a quadratic covariance uncertainty penalty. - [skfolio.uncertainty_set.BaseMuUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.BaseMuUncertaintySet.html.md): Base class for all Mu Uncertainty Set estimators in `skfolio`. - [skfolio.uncertainty_set.BaseCovarianceUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.BaseCovarianceUncertaintySet.html.md): Base class for all Covariance Uncertainty Set estimators in `skfolio`. - [skfolio.uncertainty_set.EmpiricalMuUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.EmpiricalMuUncertaintySet.html.md): Empirical Mu Uncertainty Set. - [skfolio.uncertainty_set.EmpiricalCovarianceUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.EmpiricalCovarianceUncertaintySet.html.md): Empirical Covariance Uncertainty set. - [skfolio.uncertainty_set.BootstrapMuUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.BootstrapMuUncertaintySet.html.md): Bootstrap Mu Uncertainty set. - [skfolio.uncertainty_set.BootstrapCovarianceUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.BootstrapCovarianceUncertaintySet.html.md): Bootstrap Covariance Uncertainty set. - [skfolio.uncertainty_set.OrthogonalMuUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.OrthogonalMuUncertaintySet.html.md): Expected return uncertainty set estimator for directions outside the factor span. - [skfolio.uncertainty_set.OrthogonalCovarianceUncertaintySet](https://skfolio.org/generated/skfolio.uncertainty_set.OrthogonalCovarianceUncertaintySet.html.md): Covariance uncertainty set estimator for directions outside the factor span. - [skfolio.pre_selection.DropCorrelated](https://skfolio.org/generated/skfolio.pre_selection.DropCorrelated.html.md): Transformer for dropping highly correlated assets. - [skfolio.pre_selection.DropZeroVariance](https://skfolio.org/generated/skfolio.pre_selection.DropZeroVariance.html.md): Transformer for dropping assets with near-zero variance. - [skfolio.pre_selection.SelectKExtremes](https://skfolio.org/generated/skfolio.pre_selection.SelectKExtremes.html.md): Transformer for selecting the `k` best or worst assets. - [skfolio.pre_selection.SelectNonDominated](https://skfolio.org/generated/skfolio.pre_selection.SelectNonDominated.html.md): Transformer for selecting non dominated assets. - [skfolio.pre_selection.SelectComplete](https://skfolio.org/generated/skfolio.pre_selection.SelectComplete.html.md): Transformer to select assets with complete data across the entire observation - [skfolio.pre_selection.SelectNonExpiring](https://skfolio.org/generated/skfolio.pre_selection.SelectNonExpiring.html.md): Transformer to select assets that do not expire within a specified lookahead period - [skfolio.linear_model.BaseCSLinearModel](https://skfolio.org/generated/skfolio.linear_model.BaseCSLinearModel.html.md): Base class for all cross-sectional linear model estimators. - [skfolio.linear_model.CSLinearRegression](https://skfolio.org/generated/skfolio.linear_model.CSLinearRegression.html.md): Cross-sectional weighted least squares regression. - [skfolio.linear_model.CSLinearRegressorWrapper](https://skfolio.org/generated/skfolio.linear_model.CSLinearRegressorWrapper.html.md): Cross-sectional regression based on a scikit-learn regressor. - [skfolio.model_selection.BaseCombinatorialCV](https://skfolio.org/generated/skfolio.model_selection.BaseCombinatorialCV.html.md): Base class for all combinatorial cross-validators. - [skfolio.model_selection.WalkForward](https://skfolio.org/generated/skfolio.model_selection.WalkForward.html.md): Walk Forward Cross-Validator. - [skfolio.model_selection.CombinatorialPurgedCV](https://skfolio.org/generated/skfolio.model_selection.CombinatorialPurgedCV.html.md): Combinatorial Purged Cross-Validation. - [skfolio.model_selection.MultipleRandomizedCV](https://skfolio.org/generated/skfolio.model_selection.MultipleRandomizedCV.html.md): Multiple Randomized Cross-Validation. - [skfolio.model_selection.OnlineGridSearch](https://skfolio.org/generated/skfolio.model_selection.OnlineGridSearch.html.md): Online exhaustive hyperparameter search over a parameter grid. - [skfolio.model_selection.OnlineRandomizedSearch](https://skfolio.org/generated/skfolio.model_selection.OnlineRandomizedSearch.html.md): Online randomized search on hyperparameters. - [skfolio.model_selection.CovarianceForecastEvaluation](https://skfolio.org/generated/skfolio.model_selection.CovarianceForecastEvaluation.html.md): Out-of-sample covariance forecast evaluation. - [skfolio.model_selection.CovarianceForecastComparison](https://skfolio.org/generated/skfolio.model_selection.CovarianceForecastComparison.html.md): Side-by-side comparison of covariance forecast evaluations. - [skfolio.model_selection.cross_val_predict](https://skfolio.org/generated/skfolio.model_selection.cross_val_predict.html.md): Generate cross-validated `Portfolios` estimates. - [skfolio.model_selection.online_predict](https://skfolio.org/generated/skfolio.model_selection.online_predict.html.md): Generate out-of-sample portfolios using online learning. - [skfolio.model_selection.online_score](https://skfolio.org/generated/skfolio.model_selection.online_score.html.md): Score an online estimator using walk-forward evaluation. - [skfolio.model_selection.online_covariance_forecast_evaluation](https://skfolio.org/generated/skfolio.model_selection.online_covariance_forecast_evaluation.html.md): Evaluate out-of-sample covariance forecast quality. - [skfolio.model_selection.covariance_forecast_evaluation](https://skfolio.org/generated/skfolio.model_selection.covariance_forecast_evaluation.html.md): Evaluate out-of-sample covariance forecast quality using walk-forward - [skfolio.model_selection.optimal_folds_number](https://skfolio.org/generated/skfolio.model_selection.optimal_folds_number.html.md): Find the optimal number of folds (total folds and test folds) for a target - [skfolio.metrics.make_scorer](https://skfolio.org/generated/skfolio.metrics.make_scorer.html.md): Make a scorer from a [measure](https://skfolio.org/api.html.md#measures-ref), a portfolio score - [skfolio.metrics.diagonal_calibration_loss](https://skfolio.org/generated/skfolio.metrics.diagonal_calibration_loss.html.md): Diagonal calibration loss. - [skfolio.metrics.diagonal_calibration_ratio](https://skfolio.org/generated/skfolio.metrics.diagonal_calibration_ratio.html.md): Diagonal calibration ratio based on marginal variances. - [skfolio.metrics.exceedance_rate](https://skfolio.org/generated/skfolio.metrics.exceedance_rate.html.md): Exceedance rate for chi-squared calibration statistics. - [skfolio.metrics.mahalanobis_calibration_loss](https://skfolio.org/generated/skfolio.metrics.mahalanobis_calibration_loss.html.md): Mahalanobis calibration loss. - [skfolio.metrics.mahalanobis_calibration_ratio](https://skfolio.org/generated/skfolio.metrics.mahalanobis_calibration_ratio.html.md): Mahalanobis calibration ratio. - [skfolio.metrics.portfolio_variance_calibration_loss](https://skfolio.org/generated/skfolio.metrics.portfolio_variance_calibration_loss.html.md): Portfolio variance calibration loss. - [skfolio.metrics.portfolio_variance_calibration_ratio](https://skfolio.org/generated/skfolio.metrics.portfolio_variance_calibration_ratio.html.md): Portfolio variance calibration ratio. - [skfolio.metrics.portfolio_variance_qlike_loss](https://skfolio.org/generated/skfolio.metrics.portfolio_variance_qlike_loss.html.md): QLIKE loss for a projected portfolio variance forecast [[1]](#r7dedfcdc36e0-1). - [skfolio.metrics.qlike_loss](https://skfolio.org/generated/skfolio.metrics.qlike_loss.html.md): QLIKE loss for univariate variance forecasts. - [skfolio.datasets.load_sp500_dataset](https://skfolio.org/generated/skfolio.datasets.load_sp500_dataset.html.md): Load the prices of 20 assets from the S&P 500 Index. - [skfolio.datasets.load_sp500_index](https://skfolio.org/generated/skfolio.datasets.load_sp500_index.html.md): Load the prices of the S&P 500 Index. - [skfolio.datasets.load_factors_dataset](https://skfolio.org/generated/skfolio.datasets.load_factors_dataset.html.md): Load the prices of 5 factor ETFs. - [skfolio.datasets.load_ftse100_dataset](https://skfolio.org/generated/skfolio.datasets.load_ftse100_dataset.html.md): Load the prices of 64 assets from the FTSE 100 Index composition. - [skfolio.datasets.load_nasdaq_dataset](https://skfolio.org/generated/skfolio.datasets.load_nasdaq_dataset.html.md): Load the prices of 1455 assets from the NASDAQ Composite Index. - [skfolio.datasets.load_sp500_implied_vol_dataset](https://skfolio.org/generated/skfolio.datasets.load_sp500_implied_vol_dataset.html.md): Load the 3 months ATM implied volatility of the 20 assets from the - [skfolio.datasets.make_synthetic_characteristics](https://skfolio.org/generated/skfolio.datasets.make_synthetic_characteristics.html.md): Generate a synthetic characteristics `AssetPanel` - [skfolio.preprocessing.BaseCSTransformer](https://skfolio.org/generated/skfolio.preprocessing.BaseCSTransformer.html.md): Base class for all cross-sectional transformers in skfolio. - [skfolio.preprocessing.CSGaussianRankScaler](https://skfolio.org/generated/skfolio.preprocessing.CSGaussianRankScaler.html.md): Cross-sectional rank Gaussianization. - [skfolio.preprocessing.CSPercentileRankScaler](https://skfolio.org/generated/skfolio.preprocessing.CSPercentileRankScaler.html.md): Cross-sectional percentile rank. - [skfolio.preprocessing.CSStandardScaler](https://skfolio.org/generated/skfolio.preprocessing.CSStandardScaler.html.md): Cross-sectional standardization. - [skfolio.preprocessing.CSTanhShrinker](https://skfolio.org/generated/skfolio.preprocessing.CSTanhShrinker.html.md): Cross-sectional tanh outlier shrinker. - [skfolio.preprocessing.CSWinsorizer](https://skfolio.org/generated/skfolio.preprocessing.CSWinsorizer.html.md): Cross-sectional winsorization. - [skfolio.preprocessing.prices_to_returns](https://skfolio.org/generated/skfolio.preprocessing.prices_to_returns.html.md): Transform a DataFrame of prices to linear or logarithmic returns. - [skfolio.utils.tools.AutoEnum](https://skfolio.org/generated/skfolio.utils.tools.AutoEnum.html.md): Base Enum class used in `skfolio`. - [skfolio.utils.tools.cached_property_slots](https://skfolio.org/generated/skfolio.utils.tools.cached_property_slots.html.md): Cached property decorator for slots. - [skfolio.utils.tools.apply_window_size](https://skfolio.org/generated/skfolio.utils.tools.apply_window_size.html.md): Return the last `window_size` observations from the array X. - [skfolio.utils.tools.args_names](https://skfolio.org/generated/skfolio.utils.tools.args_names.html.md): Returns the argument names of a function. - [skfolio.utils.tools.bisection](https://skfolio.org/generated/skfolio.utils.tools.bisection.html.md): Generator to bisect a list of arrays. - [skfolio.utils.tools.cache_method](https://skfolio.org/generated/skfolio.utils.tools.cache_method.html.md): Decorator that caches class method results into a class dictionary. - [skfolio.utils.tools.check_estimator](https://skfolio.org/generated/skfolio.utils.tools.check_estimator.html.md): Check the estimator type and return its cloned version if provided, otherwise - [skfolio.utils.tools.deduplicate_names](https://skfolio.org/generated/skfolio.utils.tools.deduplicate_names.html.md): Rename duplicated names by appending “_{duplicate_nb}” at the end. - [skfolio.utils.tools.default_asset_names](https://skfolio.org/generated/skfolio.utils.tools.default_asset_names.html.md): Default asset names are `["x0", "x1", ..., "x(n_assets - 1)"]`. - [skfolio.utils.tools.fit_and_predict](https://skfolio.org/generated/skfolio.utils.tools.fit_and_predict.html.md): Fit the estimator and predict values for a given dataset split. - [skfolio.utils.tools.fit_single_estimator](https://skfolio.org/generated/skfolio.utils.tools.fit_single_estimator.html.md): Fit (or partial-fit) an estimator on a subset of the data. - [skfolio.utils.tools.format_measure](https://skfolio.org/generated/skfolio.utils.tools.format_measure.html.md): Format a measure number into a user-friendly string. - [skfolio.utils.tools.get_feature_names](https://skfolio.org/generated/skfolio.utils.tools.get_feature_names.html.md): Get feature names from X. - [skfolio.utils.tools.half_life_to_decay_factor](https://skfolio.org/generated/skfolio.utils.tools.half_life_to_decay_factor.html.md): Convert half-life to exponential decay factor. - [skfolio.utils.tools.input_to_array](https://skfolio.org/generated/skfolio.utils.tools.input_to_array.html.md): Convert a collection of items (array-like or dictionary) into - [skfolio.utils.tools.optimal_rounding_decimals](https://skfolio.org/generated/skfolio.utils.tools.optimal_rounding_decimals.html.md): Return the optimal rounding decimal number for a user-friendly formatting. - [skfolio.utils.tools.safe_indexing](https://skfolio.org/generated/skfolio.utils.tools.safe_indexing.html.md): Return rows, items or columns of X using indices. - [skfolio.utils.tools.safe_split](https://skfolio.org/generated/skfolio.utils.tools.safe_split.html.md): Create subset of dataset. - [skfolio.utils.tools.validate_input_list](https://skfolio.org/generated/skfolio.utils.tools.validate_input_list.html.md): Convert a list of items (asset indices or asset names) into a list of - [skfolio.utils.stats.NBinsMethod](https://skfolio.org/generated/skfolio.utils.stats.NBinsMethod.html.md): Enumeration of the Number of Bins Methods. - [skfolio.utils.stats.assert_is_distance](https://skfolio.org/generated/skfolio.utils.stats.assert_is_distance.html.md): Raises an error if the matrix is not a distance matrix. - [skfolio.utils.stats.assert_is_square](https://skfolio.org/generated/skfolio.utils.stats.assert_is_square.html.md): Raises an error if the matrix is not square. - [skfolio.utils.stats.assert_is_symmetric](https://skfolio.org/generated/skfolio.utils.stats.assert_is_symmetric.html.md): Raises an error if the matrix is not symmetric. - [skfolio.utils.stats.combination_by_index](https://skfolio.org/generated/skfolio.utils.stats.combination_by_index.html.md): Retrieve the k-combination at a given lexicographic position without enumerating - [skfolio.utils.stats.commutation_matrix](https://skfolio.org/generated/skfolio.utils.stats.commutation_matrix.html.md): Compute the commutation matrix. - [skfolio.utils.stats.compute_optimal_n_clusters](https://skfolio.org/generated/skfolio.utils.stats.compute_optimal_n_clusters.html.md): Compute the optimal number of clusters based on Two-Order Difference to Gap - [skfolio.utils.stats.corr_to_cov](https://skfolio.org/generated/skfolio.utils.stats.corr_to_cov.html.md): Convert a correlation matrix to a covariance matrix given its - [skfolio.utils.stats.cov_nearest](https://skfolio.org/generated/skfolio.utils.stats.cov_nearest.html.md): Compute the nearest covariance matrix that is positive definite and with a - [skfolio.utils.stats.cov_to_corr](https://skfolio.org/generated/skfolio.utils.stats.cov_to_corr.html.md): Convert a covariance matrix to a correlation matrix. - [skfolio.utils.stats.cs_pearson_correlation](https://skfolio.org/generated/skfolio.utils.stats.cs_pearson_correlation.html.md): Weighted cross-sectional Pearson correlation. - [skfolio.utils.stats.cs_rank](https://skfolio.org/generated/skfolio.utils.stats.cs_rank.html.md): Cross-sectional rank along an axis. - [skfolio.utils.stats.cs_spearman_correlation](https://skfolio.org/generated/skfolio.utils.stats.cs_spearman_correlation.html.md): Cross-sectional Spearman rank correlation. - [skfolio.utils.stats.inverse_multiply](https://skfolio.org/generated/skfolio.utils.stats.inverse_multiply.html.md): Multiply the inverse of matrix a by matrix b. - [skfolio.utils.stats.inverse_volatility_weights](https://skfolio.org/generated/skfolio.utils.stats.inverse_volatility_weights.html.md): Inverse-volatility portfolio weights from a covariance matrix. - [skfolio.utils.stats.safe_cholesky](https://skfolio.org/generated/skfolio.utils.stats.safe_cholesky.html.md): Compute a Cholesky factor $L$ from covariance $\Sigma$. - [skfolio.utils.stats.is_cholesky_dec](https://skfolio.org/generated/skfolio.utils.stats.is_cholesky_dec.html.md): Returns True if Cholesky decomposition can be computed. - [skfolio.utils.stats.minimize_relative_weight_deviation](https://skfolio.org/generated/skfolio.utils.stats.minimize_relative_weight_deviation.html.md): Apply weight constraints to an initial array of weights by minimizing the relative - [skfolio.utils.stats.multiply_by_inverse](https://skfolio.org/generated/skfolio.utils.stats.multiply_by_inverse.html.md): Multiply matrix a by the inverse of matrix b. - [skfolio.utils.stats.n_bins_freedman](https://skfolio.org/generated/skfolio.utils.stats.n_bins_freedman.html.md): Compute the optimal histogram bin size using the Freedman-Diaconis rule [[1]](#r8d5b646da1d1-1). - [skfolio.utils.stats.n_bins_knuth](https://skfolio.org/generated/skfolio.utils.stats.n_bins_knuth.html.md): Compute the optimal histogram bin size using Knuth’s rule [[1]](#r8c3fe88ee915-1). - [skfolio.utils.stats.rand_weights](https://skfolio.org/generated/skfolio.utils.stats.rand_weights.html.md): Produces n random weights that sum to one from a uniform distribution - [skfolio.utils.stats.rand_weights_dirichlet](https://skfolio.org/generated/skfolio.utils.stats.rand_weights_dirichlet.html.md): Produces n random weights that sum to one from a Dirichlet distribution - [skfolio.utils.stats.sample_unique_subsets](https://skfolio.org/generated/skfolio.utils.stats.sample_unique_subsets.html.md): Generate unique k-element subsets from a universe of size n using combinatorial - [skfolio.utils.stats.squared_mahalanobis_dist](https://skfolio.org/generated/skfolio.utils.stats.squared_mahalanobis_dist.html.md): Squared Mahalanobis distance via Cholesky decomposition. - [skfolio.utils.stats.squared_standardized_euclidean_dist](https://skfolio.org/generated/skfolio.utils.stats.squared_standardized_euclidean_dist.html.md): Squared standardized Euclidean distance. - [skfolio.utils.stats.symmetric_step_up_matrix](https://skfolio.org/generated/skfolio.utils.stats.symmetric_step_up_matrix.html.md): Compute the Symmetric step-up matrix M such that `M @ np.ones(n2) = np.ones(n1)`. - [skfolio.utils.stats.symmetrize](https://skfolio.org/generated/skfolio.utils.stats.symmetrize.html.md): In-place symmetrization: $M \leftarrow (M + M^T) / 2$. - [skfolio.distribution.BaseDistribution](https://skfolio.org/generated/skfolio.distribution.BaseDistribution.html.md): Base Distribution Estimator. - [skfolio.distribution.SelectionCriterion](https://skfolio.org/generated/skfolio.distribution.SelectionCriterion.html.md): Enum representing the selection criteria. - [skfolio.distribution.BaseUnivariateDist](https://skfolio.org/generated/skfolio.distribution.BaseUnivariateDist.html.md): Base Univariate Distribution Estimator. - [skfolio.distribution.Gaussian](https://skfolio.org/generated/skfolio.distribution.Gaussian.html.md): Gaussian Distribution Estimation. - [skfolio.distribution.StudentT](https://skfolio.org/generated/skfolio.distribution.StudentT.html.md): Student’s t Distribution Estimation. - [skfolio.distribution.JohnsonSU](https://skfolio.org/generated/skfolio.distribution.JohnsonSU.html.md): Johnson SU Distribution Estimation. - [skfolio.distribution.NormalInverseGaussian](https://skfolio.org/generated/skfolio.distribution.NormalInverseGaussian.html.md): Normal Inverse Gaussian Distribution Estimation. - [skfolio.distribution.select_univariate_dist](https://skfolio.org/generated/skfolio.distribution.select_univariate_dist.html.md): Select the optimal univariate distribution estimator based on an information - [skfolio.distribution.BaseMultivariateDist](https://skfolio.org/generated/skfolio.distribution.BaseMultivariateDist.html.md): Base class for Multivariate Distribution Estimators. - [skfolio.distribution.VineCopula](https://skfolio.org/generated/skfolio.distribution.VineCopula.html.md): Regular Vine Copula Estimator. - [skfolio.distribution.DependenceMethod](https://skfolio.org/generated/skfolio.distribution.DependenceMethod.html.md): Enumeration of methods to measure bivariate dependence. - [skfolio.distribution.BaseBivariateCopula](https://skfolio.org/generated/skfolio.distribution.BaseBivariateCopula.html.md): Base class for Bivariate Copula Estimators. - [skfolio.distribution.GaussianCopula](https://skfolio.org/generated/skfolio.distribution.GaussianCopula.html.md): Bivariate Gaussian Copula Estimation. - [skfolio.distribution.StudentTCopula](https://skfolio.org/generated/skfolio.distribution.StudentTCopula.html.md): Bivariate Student’s t Copula Estimation. - [skfolio.distribution.ClaytonCopula](https://skfolio.org/generated/skfolio.distribution.ClaytonCopula.html.md): Bivariate Clayton Copula Estimation. - [skfolio.distribution.GumbelCopula](https://skfolio.org/generated/skfolio.distribution.GumbelCopula.html.md): Bivariate Gumbel Copula Estimation. - [skfolio.distribution.JoeCopula](https://skfolio.org/generated/skfolio.distribution.JoeCopula.html.md): Bivariate Joe Copula Estimation. - [skfolio.distribution.IndependentCopula](https://skfolio.org/generated/skfolio.distribution.IndependentCopula.html.md): Bivariate Independent Copula (also called the product copula). - [skfolio.distribution.compute_pseudo_observations](https://skfolio.org/generated/skfolio.distribution.compute_pseudo_observations.html.md): Compute pseudo-observations by ranking each column of the data and scaling the - [skfolio.distribution.empirical_tail_concentration](https://skfolio.org/generated/skfolio.distribution.empirical_tail_concentration.html.md): Compute empirical tail concentration for the two variables in X. - [skfolio.distribution.plot_tail_concentration](https://skfolio.org/generated/skfolio.distribution.plot_tail_concentration.html.md): Plot the empirical tail concentration curves. - [skfolio.distribution.select_bivariate_copula](https://skfolio.org/generated/skfolio.distribution.select_bivariate_copula.html.md): Select the best bivariate copula from a list of candidates using an information - [skfolio.distribution.CopulaRotation](https://skfolio.org/generated/skfolio.distribution.CopulaRotation.html.md): Enum representing the rotation (in degrees) to apply to a bivariate copula. - [Alpha Eval Cumulative Ic.Inc](https://skfolio.org/_static/factor_model/fragments/alpha_eval_cumulative_ic.inc.html.md):
- [Alpha Eval Cumulative Returns.Inc](https://skfolio.org/_static/factor_model/fragments/alpha_eval_cumulative_returns.inc.html.md):
- [Alpha Eval Factor Correlation.Inc](https://skfolio.org/_static/factor_model/fragments/alpha_eval_factor_correlation.inc.html.md):
- [Alpha Realized Return Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/alpha_realized_return_contrib.inc.html.md):
- [Attribution Predicted Exposure.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_predicted_exposure.inc.html.md):
- [Attribution Predicted Return Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_predicted_return_contrib.inc.html.md):
- [Attribution Predicted Return Vs Vol Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_predicted_return_vs_vol_contrib.inc.html.md):
- [Attribution Predicted Vol Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_predicted_vol_contrib.inc.html.md):
- [Attribution Realized Exposure.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_realized_exposure.inc.html.md):
- [Attribution Realized Return Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_realized_return_contrib.inc.html.md):
- [Attribution Realized Return Vs Vol Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_realized_return_vs_vol_contrib.inc.html.md):
- [Attribution Realized Vol Contrib.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_realized_vol_contrib.inc.html.md):
- [Attribution Rolling Realized Exposure.Inc](https://skfolio.org/_static/factor_model/fragments/attribution_rolling_realized_exposure.inc.html.md):
- [Covariance Cmp Calibration.Inc](https://skfolio.org/_static/factor_model/fragments/covariance_cmp_calibration.inc.html.md):
- [Covariance Cmp Qlike Loss.Inc](https://skfolio.org/_static/factor_model/fragments/covariance_cmp_qlike_loss.inc.html.md):
- [Covariance Eval Calibration.Inc](https://skfolio.org/_static/factor_model/fragments/covariance_eval_calibration.inc.html.md):
- [Factor Model Cs Regression Scores Adjusted R2.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_cs_regression_scores_adjusted_r2.inc.html.md):
- [Factor Model Cs Regression T Stat Exceedance Rate.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_cs_regression_t_stat_exceedance_rate.inc.html.md):
- [Factor Model Cumulative Exposure Ic.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_cumulative_exposure_ic.inc.html.md):
- [Factor Model Exposure Correlation.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_exposure_correlation.inc.html.md):
- [Factor Model Exposure Stability.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_exposure_stability.inc.html.md):
- [Factor Model Factor Cumulative Returns.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_factor_cumulative_returns.inc.html.md):
- [Factor Model Factor Forecast Correlation.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_factor_forecast_correlation.inc.html.md):
- [Factor Model Factor Forecast Volatilities.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_factor_forecast_volatilities.inc.html.md):
- [Factor Model Idio Calibration.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_idio_calibration.inc.html.md):
- [Factor Model Idio Vol Ic.Inc](https://skfolio.org/_static/factor_model/fragments/factor_model_idio_vol_ic.inc.html.md):
- [Mpp Composition.Inc](https://skfolio.org/_static/factor_model/fragments/mpp_composition.inc.html.md):
- [Mpp Cumulative Returns.Inc](https://skfolio.org/_static/factor_model/fragments/mpp_cumulative_returns.inc.html.md):
- [Alpha Eval Ic Summary.Inc](https://skfolio.org/_static/factor_model/tables/alpha_eval_ic_summary.inc.html.md):
- [Alpha Eval Portfolio Summary.Inc](https://skfolio.org/_static/factor_model/tables/alpha_eval_portfolio_summary.inc.html.md):
- [Attribution Predicted Factors Head.Inc](https://skfolio.org/_static/factor_model/tables/attribution_predicted_factors_head.inc.html.md):
- [Attribution Predicted Families.Inc](https://skfolio.org/_static/factor_model/tables/attribution_predicted_families.inc.html.md):
- [Attribution Predicted Summary.Inc](https://skfolio.org/_static/factor_model/tables/attribution_predicted_summary.inc.html.md):
- [Attribution Realized Factors Head.Inc](https://skfolio.org/_static/factor_model/tables/attribution_realized_factors_head.inc.html.md):
- [Attribution Realized Families.Inc](https://skfolio.org/_static/factor_model/tables/attribution_realized_families.inc.html.md):
- [Attribution Realized Summary.Inc](https://skfolio.org/_static/factor_model/tables/attribution_realized_summary.inc.html.md):
- [Attribution Rolling Realized Summary.Inc](https://skfolio.org/_static/factor_model/tables/attribution_rolling_realized_summary.inc.html.md):
- [Covariance Comparison Summary.Inc](https://skfolio.org/_static/factor_model/tables/covariance_comparison_summary.inc.html.md):
- [Covariance Evaluation Summary.Inc](https://skfolio.org/_static/factor_model/tables/covariance_evaluation_summary.inc.html.md):
- [Factor Model Exposure Ic Summary.Inc](https://skfolio.org/_static/factor_model/tables/factor_model_exposure_ic_summary.inc.html.md):
- [Style Factor Summary.Inc](https://skfolio.org/_static/factor_model/tables/style_factor_summary.inc.html.md):
--- For more comprehensive documentation, see [llms-full.txt](https://skfolio.org/llms-full.txt)