portfolio.optim {tseries}R Documentation

Portfolio Optimization

Description

Computes an efficient portfolio from the given return series x in the mean-variance sense.

Usage

portfolio.optim (x, pm = mean(x), riskless = FALSE, shorts = FALSE, rf = 0.0)

Arguments

x a numeric matrix or multivariate time series consisting of a series of returns.
pm the desired mean portfolio return.
riskless a logical indicating whether there is a riskless lending and borrowing rate.
shorts a logical indicating whether shortsales on the risky securities are allowed.
rf the riskfree interest rate.

Details

The computed portfolio has the desired expected return pm and no other portfolio exists, which has the same mean return, but a smaller variance. 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.

Value

A list containing the following components:

pw the portfolio weights.
px the returns of the overall portfolio.
pm the expected portfolio return.
ps the standared deviation of the portfolio returns.

Author(s)

A. Trapletti

References

E. J. Elton and M. J. Gruber (1991): Modern Portfolio Theory and Investment Analysis, 4th Edition, Wiley, NY, pp. 65-93.

C. Huang and R. H. Litzenberger (1988): Foundations for Financial Economics, Elsevier, NY, pp. 59-82.

See Also

solve.QP

Examples

x <- rnorm (1000)
dim(x) <- c(500,2)
res <- portfolio.optim (x)
res$pw