Class_MeanVar_portfolio

<p>Class MeanVar_portfolio is designed to construct mean-variance portfolios
with provided estimators of the mean vector, covariance matrix, and
inverse covariance matrix. It includes the following elements:</p>

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 <doi:10.1016/j.ejor.2017.09.028>, 2019 <doi:10.1109/TSP.2019.2929964>,
2020 <doi:10.1109/TSP.2020.3037369>, 2021 <doi:10.1080/07350015.2021.2004897>)
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) <doi:10.1080/14697688.2020.1748214>.

Dmitry Otryakhin

HDShOP

High-Dimensional Shrinkage Optimal Portfolios

Taras Bodnar

Solomiia Dmytriv

Yarema Okhrin

Nestor Parolya

Class_MeanVar_portfolio function


<table class="table">
<tr><td>Element</td><td>Description</td></tr>
<tr><td>call</td><td>the function call with which it was created</td></tr>
<tr><td>cov_mtrx</td><td>the sample covariance matrix of the asset returns</td></tr>
<tr><td>inv_cov_mtrx</td><td>the inverse of the sample covariance matrix</td></tr>
<tr><td>means</td><td>sample mean vector of the asset returns</td></tr>
<tr><td>weights</td><td>portfolio weights</td></tr>
<tr><td>Port_Var</td><td>portfolio variance</td></tr>
<tr><td>Port_mean_return</td><td>expected portfolio return</td></tr>
<tr><td>Sharpe</td><td>portfolio Sharpe ratio</td></tr>
</table><p></p><p></p>

Slots

S3 class MeanVar_portfolio — Class_MeanVar_portfolio


<table class='table'>
<tr><td>Element</td><td>Description</td></tr>
<tr><td>call</td><td>the function call with which it was created</td></tr>
<tr><td>cov_mtrx</td><td>the sample covariance matrix of the asset returns</td></tr>
<tr><td>inv_cov_mtrx</td><td>the inverse of the sample covariance matrix</td></tr>
<tr><td>means</td><td>sample mean vector of the asset returns</td></tr>
<tr><td>weights</td><td>portfolio weights</td></tr>
<tr><td>Port_Var</td><td>portfolio variance</td></tr>
<tr><td>Port_mean_return</td><td>expected portfolio return</td></tr>
<tr><td>Sharpe</td><td>portfolio Sharpe ratio</td></tr>
</table>



Class_MeanVar_portfolio: S3 class MeanVar_portfolio

Description

Arguments

Slots

See Also

Element	Description
call	the function call with which it was created
cov_mtrx	the sample covariance matrix of the asset returns
inv_cov_mtrx	the inverse of the sample covariance matrix
means	sample mean vector of the asset returns
weights	portfolio weights
Port_Var	portfolio variance
Port_mean_return	expected portfolio return
Sharpe	portfolio Sharpe ratio