wGMVOverlapping {DOSPortfolio}

Dynamic optimal shrinkage estimator of the weights of the global minimum variance portfolio when overlapping samples are used.

Description

The function implements the dynamic shrinkage estimator of the weights of the global minimum-variance portfolio when the overlapping samples are used as given in Eq. (2.23) of Bodnar et al. (2021).

Usage

wGMVOverlapping(data, reallocation_points, target_portfolio, relative_loss)

Arguments

data

an n by p matrix of asset returns. Columns represent different assets rows are observations, where n>p, containing, for instance, log-returns.

reallocation_points

a vector of reallocation points. The reallocation points determine when the holding portfolio should be reconstructed and it is weights should be recomputed.

target_portfolio

a vector which determines the weights of the target portfolio used when the shrinkage estimator of the global minimum variance portfolio is constructed for the first time.

relative_loss

possibly a numeric or NULL. The initial value of the relative loss in the variance of the target portfolio. If it is NULL, then it will be initialized with the first subsample and the function r0Strategy.

Value

a matrix of the constructed weights at each reallocation point of the dynamic shrinkage estimator of the global minimum variance portfolio when overlapping samples are used.

References

Bodnar T, Parolya N, Thorsén E (2021). “Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio.” arXiv preprint arXiv:2106.02131. https://arxiv.org/abs/2106.02131.

See Also

wGMVNonOverlapping

Examples

n <- 200*2
p <- 80
reallocation_points <- c(199)
data <- matrix(rt(n*p, df=5), ncol=p, nrow=n)
target_portfolio <- as.vector(rep(1,p))/p
wGMVOverlapping(data, reallocation_points, target_portfolio, 1)