returns: Computing expected returns and their covariance matrix

In RcmdrPlugin.RiskDemo: R Commander Plug-in for Risk Demonstration

Computing expected returns and their covariance matrix

Description

Computing expected returns and their covariance matrix when the returns are lognormal.

Usage

returns(volvec, indexvol, beta)

Arguments

volvec	vector of volatilities
indexvol	volatility of the portfolio index
beta	vector of betas

Details

The arguments are given in decimals. The single index model is used to compute the covariance matrix of a multivariate normal distribution. The mean vector is assumed to be zero. The properties of the log-normal distribution are then used to compute the mean vector and covariance matrix of the corresponding multivariate log-normal distribution.

Value

mean	vector of expected returns
cov	covariance matrix of returns

Author(s)

Arto Luoma <[e-mail]>

References

Bodie, Kane, and Marcus (2014) Investments, 10th Global Edition, McGraw-Hill Education, (see Section 8.2 The Single-Index Model).

Examples

returns(volvec=c(0.1,0.2,0.3),indexvol=0.2, beta=c(0.5,-0.1,1.1)) 

RcmdrPlugin.RiskDemo documentation built on June 22, 2024, 7:06 p.m.