x
in the mean-variance sense.## S3 method for class 'default':
portfolio.optim(x, pm = mean(x), riskless = FALSE,
shorts = FALSE, rf = 0.0, reslow = NULL, reshigh = NULL,
covmat = cov(x), ...)
pm
and
no other portfolio exists, which has the same mean return, but a
smaller variance. Inequality restrictions of the form $w_l \le w
\le w_h$ can be imposed using the reslow
and
reshigh
vectors. An alternative covariance matrix estimate can
be supplied via the covmat
argument. To solve the quadratic
program, solve.QP
is used. portfolio.optim
is a generic function with methods for
multivariate "ts"
and default
for matrix.
Missing values are not allowed.
C. Huang and R. H. Litzenberger (1988): Foundations for Financial Economics, Elsevier, NY, pp. 59-82.
solve.QP
x <- rnorm(1000)
dim(x) <- c(500,2)
res <- portfolio.optim(x)
res$pw
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