HDShOP-package: A set of tools for shrinkage estimation of mean-variance...
In HDShOP: High-Dimensional Shrinkage Optimal Portfolios
HDShOP-package R Documentation
A set of tools for shrinkage estimation of mean-variance optimal portfolios
Description
Package HDShOP has the following three important functions:
MVShrinkPortfolio, CovarEstim and
MeanEstim. MVShrinkPortfolio creates mean-variance
portfolios using shrinkage estimation methods for portfolio weights.
CovarEstim computes several estimators of the covariance matrix, while
MeanEstim computes several estimators of the mean vector. Each of these
three functions is supplied a name of the method used to perform the
estimation. All portfolios are stored in objects of class MeanVar_portfolio
and some have a subclass, specific to their kind, that inherits from
MeanVar_portfolio. For the latter class constructor, validator and
helper functions are available, so that custom mean-variance portfolios
may be coded by users.
Methods
MeanEstim: \insertCiteBOP2019HDShOP, James-Stein and Bayes-Stein
estimators \insertCiteJorion1986HDShOP.
CovarEstim: \insertCiteBGP2014HDShOP, \insertCiteLW2020HDShOP.
MVShrinkPortfolio: \insertCiteBDOPS2021HDShOP,
\insertCiteBDPS2019HDShOP.
MeanVar_portfolio.
Author(s)
Maintainer: Dmitry Otryakhin d.otryakhin.acad@protonmail.ch (ORCID)
Authors:
See Also
Useful links:
HDShOP documentation built on May 29, 2024, 2:20 a.m.
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| HDShOP-package | R Documentation |
A set of tools for shrinkage estimation of mean-variance optimal portfolios
Description
Package HDShOP has the following three important functions:
MVShrinkPortfolio, CovarEstim and
MeanEstim. MVShrinkPortfolio creates mean-variance
portfolios using shrinkage estimation methods for portfolio weights.
CovarEstim computes several estimators of the covariance matrix, while
MeanEstim computes several estimators of the mean vector. Each of these
three functions is supplied a name of the method used to perform the
estimation. All portfolios are stored in objects of class MeanVar_portfolio
and some have a subclass, specific to their kind, that inherits from
MeanVar_portfolio. For the latter class constructor, validator and
helper functions are available, so that custom mean-variance portfolios
may be coded by users.
Methods
MeanEstim: \insertCiteBOP2019HDShOP, James-Stein and Bayes-Stein estimators \insertCiteJorion1986HDShOP.
CovarEstim: \insertCiteBGP2014HDShOP, \insertCiteLW2020HDShOP.
MVShrinkPortfolio: \insertCiteBDOPS2021HDShOP, \insertCiteBDPS2019HDShOP.
MeanVar_portfolio.
Author(s)
Maintainer: Dmitry Otryakhin d.otryakhin.acad@protonmail.ch (ORCID)
Authors:
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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