View source: R/S3_weights_portfol.R
new_MV_portfolio_weights_BDOPS21 | R Documentation |
Constructor of mean-variance shrinkage portfolios. new_MV_portfolio_weights_BDOPS21
is for the case p<n, while new_MV_portfolio_weights_BDOPS21_pgn is for p>n, where
p is the number of assets and n is the number of observations.
For more details of the method, see MVShrinkPortfolio
.
new_MV_portfolio_weights_BDOPS21(x, gamma, b, beta) new_MV_portfolio_weights_BDOPS21_pgn(x, gamma, b, beta)
x |
a p by n matrix or a data frame of asset returns. Rows represent different assets, columns – observations. |
gamma |
a numeric variable. Coefficient of risk aversion. |
b |
a numeric variable. The weights of the target portfolio. |
beta |
a numeric variable. The confidence level for weight intervals. |
an object of class MeanVar_portfolio with subclass MV_portfolio_weights_BDOPS21.
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 |
W_mv_hat | sample estimator of the portfolio weights |
weights | shrinkage estimator of the portfolio weights |
alpha | shrinkage intensity for the weights |
Port_Var | portfolio variance |
Port_mean_return | expected portfolio return |
Sharpe | portfolio Sharpe ratio |
weight_intervals | A data frame, see details |
weight_intervals contains a shrinkage estimator of portfolio weights, asymptotic confidence intervals for the true portfolio weights, value of the test statistic and the p-value of the test on the equality of the weight of each individual asset to zero (see Section 4.3 of Bodnar, Dette, Parolya and Thorsén 2021). weight_intervals is only computed when p<n.
BDOPS2021HDShOP
\insertRefBDNT21HDShOP
# c<1 # Assets with a diagonal covariance matrix n<-3e2 # number of realizations p<-.5*n # number of assets b<-rep(1/p,p) gamma<-1 x <- matrix(data = rnorm(n*p), nrow = p, ncol = n) test <- new_MV_portfolio_weights_BDOPS21(x=x, gamma=gamma, b=b, beta=0.05) summary(test) # Assets with a non-diagonal covariance matrix Mtrx <- RandCovMtrx(p=p) x <- t(MASS::mvrnorm(n=n , mu=rep(0,p), Sigma=Mtrx)) test <- new_MV_portfolio_weights_BDOPS21(x=x, gamma=gamma, b=b, beta=0.05) str(test) # c>1 n<-2e2 # number of realizations p<-1.2*n # number of assets b<-rep(1/p,p) x <- matrix(data = rnorm(n*p), nrow = p, ncol = n) test <- new_MV_portfolio_weights_BDOPS21_pgn(x=x, gamma=gamma, b=b, beta=0.05) summary(test) # Assets with a non-diagonal covariance matrix
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