returns {RcmdrPlugin.RiskDemo} | R Documentation |
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 <arto.luoma@wippies.com>
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))
[Package RcmdrPlugin.RiskDemo version 3.2 Index]