HDShOP (version 0.1.5)

MeanVar_portfolio: A helper function for MeanVar_portfolio

Description

A user-friendly function making mean-variance portfolios for assets with customly computed covariance matrix and mean returns. The weights are computed in accordance with the formula $$\hat w_{MV} = \frac{\hat{\Sigma}^{-1} 1}{1' \hat{\Sigma}^{-1} 1} + \gamma^{-1} \hat Q \hat{\mu},$$ where \(\hat{\Sigma}\) is an estimator for the covariance matrix, \(\hat{\mu}\) is an estimator for the mean vector, \(\gamma\) is the coefficient of risk aversion, and \(\hat Q\) is given by $$\hat Q = \hat{\Sigma}^{-1} - \frac{\hat{\Sigma}^{-1} 1 1' \hat{\Sigma}^{-1}}{1' \hat{\Sigma}^{-1} 1} .$$ The computation is made by new_MeanVar_portfolio and the result is validated by validate_MeanVar_portfolio.

Usage

MeanVar_portfolio(mean_vec, cov_mtrx, gamma)

Value

Mean-variance portfolio in the form of object of S3 class MeanVar_portfolio.

Arguments

mean_vec

mean vector of asset returns provided in the form of a vector or a list.

cov_mtrx

the covariance matrix of asset returns. It could be a matrix or a data frame.

gamma

a numeric variable. Coefficient of risk aversion.

Examples

n<-3e2 # number of realizations
p<-.5*n # number of assets
gamma<-1

x <- matrix(data = rnorm(n*p), nrow = p, ncol = n)

# Simple MV portfolio
cov_mtrx <- Sigma_sample_estimator(x)
means <- rowMeans(x)

cust_port_simp <- MeanVar_portfolio(mean_vec=means,
                                    cov_mtrx=cov_mtrx, gamma=2)
str(cust_port_simp)