rbenchmark: Generate random naive benchmark portfolios

In rportfolios: Random Portfolio Generation

Description

This function generates m random long only benchmark portfolios with n investments where the sume of the weights equals a given amount. The weights are naively derived from an i.i.d. sample of truncated random variables.

Usage

rbenchmark(m, n = 2, k = n, segments = NULL, x.t = 1, 
margins = c("unif", "beta", "exp", "frechet", 
"gamma", "gev", "gpd", "gumbel", "lnorm", "logis", "norm", 
"weibull"), ...)

Arguments

m	A positive integer value for the number of portfolios
n	A positive integer for the number of investments in the portfolio
k	A positive integer for the number of non-zero exposures or cardinality
segments	A vector or list of vectors that defines the investment segments
x.t	A positive real value for the sum of the investment exposures
margins	A character value for the underlying distribution of the truncated random variable. The default is a uniform distribution
...	Other arguments passed to the random variate simulation function

Details

The function executes the function random.benchmark using the R function sapply. The result returned is the transpose of the matrix generated in the previous step.

Value

A numeric m \times n matrix. The rows are the portfolios and the columns are the investment weights for each portfolio

Author(s)

Frederick Novomestky [e-mail]

See Also

random.benchmark

Examples

###
### 100 long only portfolios of 30 investments with 30 non-zero positions
### the margins of the truncated random variables are uniform
###
p.1.matrix <- rbenchmark( 100, 30 )
###
### 100 long only portfolios of 30 investments with 10 non-zero positions
### the margins of the truncated random variables are uniform
###
p.2.matrix <- rbenchmark( 100, 30, 10 )
###
### 100 long only portfolios of 30 investments with 30 non-zero positions
### the margins of the truncated random variables are log normal
### with zero log mean and unit log standard deviation
###
p.3.matrix <- rbenchmark( 100, 30, margins="lnorm", meanlog=0, sdlog=1 )
###
### 100 long only portfolios of 30 investments with 10 non-zero positions
### the margins of the truncated random variables are log norm
### with zero log mean and unit log standard deviation
###
p.4.matrix <- rbenchmark( 100, 30, 10, margins="lnorm", meanlog=0, sdlog=1 )

rportfolios documentation built on May 2, 2019, 3:40 p.m.