Changelog
Version 6.0.0
Implements risk parity optimization based on explicit risk factors and principal components.
Implements new formulations of Gini Mean Difference, Tail Gini, Range, CVaR Range and Tail Gini Range that improves speed compared to formulations based on the owa portfolio model.
Improves the calculation of elliptical uncertainty sets for worst case optimization.
Add new functions that allow us to calculate the risk contribution per explicit risk factors and principal components.
Add new functions that allow us to plot the risk contribution per explicit risk factors and principal components.
Version 5.0.0
Implements new kind of constraints that incorporates the information from networks like the Minimum Spanning Tree and Maximally Filtered Graph into the portfolio optimization models: return-risk portfolio, owa portfolio and worst case portfolio.
Implements new kind of constraints that incorporates the information from dendrograms into the portfolio optimization models: return-risk portfolio, owa portfolio and worst case portfolio.
Improves the speed of several functions using the c++ linear algebra library Eigen and c++ eigenvalues library Spectra.
Add new functions that allow us to plot the relationship between graphs and asset allocation.
Add new functions that allow us to create constraints based on graphs information.
Add a new example about applications of networks and dendrograms constraints in portfolio optimization problems.
Fixed some errors related to HCPortfolio with constraints.
Fixed some errors in some plots.
Version 4.4.0
Implements the approximate Kurtosis model through sum of squared quadratic forms for large scale kurtosis optimization.
Add the block vectorization operator.
Version 4.3.0
Implements custom constraints for the Relaxed Risk Parity portfolio model.
Add three new methods to estimate the mean vector: James-Stein, Bayes-Stein and BOP.
Version 4.2.0
Implements constraints for the Hierarchical Equal Risk Contribution (HERC) and Nested Clustered Optimization (NCO) portfolio models.
Add the option to show risk contributions as a percentage of total risk in risk contribution plot.
Repairs some bugs.
Version 4.1.0
Implements the Relativistic Value at Risk and Relativistic Drawdown at Risk portfolio models.
Implements the Higher L-moments portfolio model function as an special case of OWA portfolio.
Adds functions to calculate L-moments.
Adds a function to calculate risk contribution constraints on asset classes.
Repairs some bugs.
Version 4.0.0
Implements Kurtosis and Semi Kurtosis portfolio models based on parametric approach.
Implements new c++ based functions to speed up kurtosis model calculations.
Repairs some bugs.
Version 3.3.0
Adds Kendall Tau and Gerber statistic as options for codependence matrix in HCPortfolio object.
Adds Gerber statistic as an option for covariance matrix estimator in Portfolio and HCPortfolio objects.
Version 3.2.0
Implements reformulations of portfolio models based on drawdowns to speed up calculations.
Adds some tests for portfolio object and hcportfolio object.
Version 3.1.0
Implements a reformulation of OWA portfolio optimization to speed up calculations.
Version 3.0.0
Implements 5 additional risk measures for mean risk model: Gini Mean Difference, Tail Gini, Range, CVaR range and Tail Gini range.
Implements 4 additional risk measures for risk parity model: Gini Mean Difference, Tail Gini, CVaR range and Tail Gini range.
Implements the OWA Portfolio Optimization model for custom vector of weights and a module to build OWA weights for some special cases.
Implements a function to plot range risk measures.
Adds the option to use Graphical Lasso, j-Logo, denoising and detoning covariance estimates.
Version 2.0.0
Implement Nested Clustered Optimization (NCO) model with four objective functions.
Implements the Relaxed Risk Parity model.
Implements the Risk Budgeting approach for Risk Parity Portfolios with constraints.
Adds the option to use custom covariance in Hierarchical Clustering Portfolios.
Version 1.0.0
Redesigns of Riskfolio-Lib interface (Only import riskfolio for all functions).
Implements Hierarchical Risk Parity (HRP) model with constraints on assets’ weights.
Implements a function that helps to build constraints for the HRP model.
Implements the Direct Bubble Hierarchical Tree (DBHT) linkage method for HRP and HERC models.
Implements a function that plots relationship among assets in a network using Minimum Spanning Tree (MST) and Planar Maximally Filtered Graph (PMFG).
Adds two new codependence measures: mutual information and lower tail dependence index.
Version 0.4.0
Implements Hierarchical Equal Risk Contribution with equally weights within clusters (HERC2).
Implements a function that help us to discretize portfolio weights into number of shares given an investment amount.
Implements the option to select the method to estimate covariance in HRP, HERC and HERC2.
Adds the option to add constraints on the number of assets and the number of effective assets.
Fixes an error in two_diff_gap_stat() when number of assets is too small.
Fixes an error on forward_regression() and backward_regression() when there is no significant feature in regression modes using p-value criterion.
Adds an example that shows how to build HERC2 portfolios.
Adds an example that shows how to build constraints on the number of assets and number of effective assets.
Version 0.3.0
Implements Hierarchical Risk Parity (HRP) and Hierarchical Equal Risk Parity (HERC).
Implements the function plot_clusters() and plot_dendrogram() that help us to identify clusters based on a distance correlation metric.
Implements the function assets_clusters() that help us to create asset classes based on hierarchical clusters.
Adds an example that shows how to build Hierarchical Risk Parity portfolios.
Adds an example that shows how to build Hierarchical Equal Risk Parity portfolios.
Version 0.2.0
Implements Logarithmic Mean Risk (Kelly Criterion) Portfolio Optimization models.
Implements the function plot_bar() that help us to plot portfolios with negative weights.
Adds the option to build dollar neutral portfolios.
Adds an example that shows how to build Logarithmic Mean Risk (Kelly Criterion) portfolios.
Adds an example that shows how to build dollar neutral portfolios.
Version 0.1.5
Adds the option to add a constraint on minimum portfolio return.
Adds an example of how to add constraints on portfolio return and risk measures.
Version 0.1.4
Adds Black Litterman with factors in two flavors: Black Litterman Bayesian model and Augmented Black Litterman model.
Implements factors_views, a function that allows to design views on risk factors for Black Litterman with factors.
Repairs some bugs.
Version 0.1.2
Adds Entropic Drawdown at Risk for Mean Risk Portfolio Optimization and Risk Parity Portfolio Optimization.
Repairs some bugs.
Version 0.1.1
Repairs some bugs in Portfolio related to Semi Variance and UCI.
Implements an option to annualize returns and risk in plot_frontier, Jupyter Notebook and Excel reports.
Adds examples using Vectorbt for Backtesting and MOSEK for large scale problems.
Version 0.1.0
Repairs some bugs in RiskFunctions.
Implements the Reports module that helps to build reports on Jupyter Notebook and Excel.
Implements plot_table, a function that resume some indicators of a portfolio.
Adds Entropic Value at Risk for Mean Risk Portfolio Optimization and Risk Parity Portfolio Optimization.
Version 0.0.7
Implements normal assumption method to estimate box and elliptical uncertainty sets for Worst Case Optimization.
Implements elliptical uncertainty sets for covariance matrix.
Adds Ulcer Index for Mean Risk Portfolio Optimization and Risk Parity Portfolio Optimization.
Implements functions to calculate Ulcer Index.
Version 0.0.6
Repairs some bugs.
Implements bootstrapping methods to estimate box and elliptical uncertainty sets for Worst Case Optimization.
Implements Worst Case Mean Variance Portfolio Optimization using box and elliptical uncertainty sets.
Version 0.0.5
Repairs some bugs.
Implements Risk Parity Portfolio Optimization for 7 convex risk measures.
Version 0.0.4
Repairs some bugs.
Update to make it compatible with cvxpy >=1.1.0
Implements Principal Component Regression for loadings matrix estimation.
Adds Akaike information criterion, Schwarz information criterion, R squared and adjusted R squared feature selection criterions in stepwise regression.
Version 0.0.3
Repairs some bugs.
Implements an option for building constraints common for all assets classes.
Version 0.0.2
Repairs some bugs.
Version 0.0.1
Implements robust and ewma estimates.
Implements Black Litterman model and risk factors models.
Implements mean risk optimization with 10 risk measures.