Last chance! 50% off unlimited learning
Sale ends in
Computing expected returns and their covariance matrix when the returns are lognormal.
returns(volvec, indexvol, beta)vector of expected returns
covariance matrix of returns
vector of volatilities
volatility of the portfolio index
vector of betas
Arto Luoma <arto.luoma@wippies.com>
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.
Bodie, Kane, and Marcus (2014) Investments, 10th Global Edition, McGraw-Hill Education, (see Section 8.2 The Single-Index Model).
returns(volvec=c(0.1,0.2,0.3),indexvol=0.2, beta=c(0.5,-0.1,1.1))
Run the code above in your browser using DataLab