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HDShOP
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Download and install HDShOP package within the R console
Install from CRAN:
install.packages("HDShOP")
Install from Github:
library("remotes")
install_github("cran/HDShOP")
Install by package version:
library("remotes")
install_version("HDShOP", "0.1.5")
Attach the package and use:
library("HDShOP")
Maintained by
Dmitry Otryakhin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-08-02
Latest Update: 2022-11-08
Description:
Constructs shrinkage estimators of high-dimensional mean-variance portfolios and performs
high-dimensional tests on optimality of a given portfolio. The techniques developed in
Bodnar et al. (2018 , 2019 ,
2020 , 2021 )
are central to the package. They provide simple and feasible estimators and tests for optimal
portfolio weights, which are applicable for 'large p and large n' situations where p is the
portfolio dimension (number of stocks) and n is the sample size. The package also includes tools
for constructing portfolios based on shrinkage estimators of the mean vector and covariance matrix
as well as a new Bayesian estimator for the Markowitz efficient frontier recently developed by
Bauder et al. (2021) .
How to cite:
Dmitry Otryakhin (2021). HDShOP: High-Dimensional Shrinkage Optimal Portfolios. R package version 0.1.5, https://cran.r-project.org/web/packages/HDShOP. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Other R packages that HDShOP depends,
imports, suggests or enhances
Complete documentation for HDShOP
Functions, R codes and Examples using
the HDShOP R package
Some associated functions: Class_MeanVar_portfolio . CovShrinkBGP14 . CovarEstim . HDShOP-package . InvCovShrinkBGP16 . MVShrinkPortfolio . MeanEstim . MeanVar_portfolio . RandCovMtrx . SP_daily_asset_returns . Sigma_sample_estimator . mean_bop19 . mean_bs . mean_js . new_GMV_portfolio_weights_BDPS19 . new_MV_portfolio_traditional . new_MV_portfolio_weights_BDOPS21 . new_MeanVar_portfolio . nonlin_shrinkLW . plot_frontier . test_MVSP . validate_MeanVar_portfolio .
Some associated R codes: BDOPS_2020.R . BOP_2019.R . Class_ExUtil_portfolio.R . HDShOP-package.R . Matrix_shrink.R . Mean_shrink.R . Plot_frontier.R . S3_custom_portfol.R . S3_tradit_portfol.R . S3_weights_portfol.R . T_alpha_statistics.R . case_c_gr_1.R . data.R . dispatchers.R . random_cov_matrix.R . Full HDShOP package functions and examples
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