returns: Computing expected returns and their covariance matrix

Description Usage Arguments Details Value Author(s) References Examples

View source: R/returns.R

Description

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

Usage

1
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

1
returns(volvec=c(0.1,0.2,0.3),indexvol=0.2, beta=c(0.5,-0.1,1.1)) 

Example output

Loading required package: rgl
Loading required package: demography
Loading required package: forecast
This is demography 1.22 

Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
4: no DISPLAY variable so Tk is not available 
$mean
[1] 0.005012521 0.020201340 0.046027860

$cov
             [,1]         [,2]         [,3]
[1,]  0.010151173 -0.002048581  0.023384248
[2,] -0.002048581  0.042476293 -0.004685185
[3,]  0.023384248 -0.004685185  0.103043079

RcmdrPlugin.RiskDemo documentation built on April 6, 2021, 5:06 p.m.