meanVariancePortfolioOptimizerQP: meanVariancePortfolioOptimizerQP

In theteetrinker/CQFFA: CQF Final Project (Portfolio Optimization)

Description

Mean Variance Portfolio Optimizer using Quadratic Programming

Usage

meanVariancePortfolioOptimizerQP(mu.vector, sigma.vector = NA,
  correl.matrix = NA, covar.matrix = NA, use.covar.matrix = FALSE,
  target.return, sum.weight = 1, min.single.weight = -100,
  max.single.weight = 100, mvp = FALSE)

Arguments

mu.vector	vector with estimated returns of investment objects
sigma.vector	vector with the volatilities of the investment objects
correl.matrix	correlation matrix of the investment objects
use.covar.matrix	use covariance matrix directly or build it via sigma vector and the correlation matrix, default is FALSE
target.return	which return level is seeked (for which the variance is minimized)
sum.weight	default is 1
min.single.weight	default is -100
max.single.weight	default is +100
asset.name	Name of assets available
covar.matrx	covariance matrix

Value

weight.risky.assets a vector with the weights of the risky assets

Examples

weights.vector          <- c(0.7,0.3)
daily.returns.data.wide <- data.frame(ref.date=c(Sys.Date()-2:0), asset1.ret=c(-0.02,0.005,0.004), asset2.ret=c(0,-0.001,0.02))
PFstats(weights.vector=weights.vector, daily.returns.data.wide=daily.returns.data.wide)

theteetrinker/CQFFA documentation built on July 17, 2019, 3:37 p.m.