[R] how to use solve.QP

[roger bos]

Zeileis,

Thanks, I didn't know about "portfolio.optim".  I wanted to see how it
works, but when I try showMethods, it doesn't show it to me.  Does
that mean I am not allowed to see the inner workings?

Thanks,

Roger

> showMethods("portfolio.optim")

Function "portfolio.optim":
<not a generic function>
> 


On Thu, 13 Jan 2005 19:58:33 +0100, Achim Zeileis
<Achim.Zeileis at wu-wien.ac.at> wrote:
> On Thu, 13 Jan 2005 13:44:58 -0500 roger bos wrote:
> 
> > At the risk of ridicule for my deficient linear algebra skills, I ask
> > for help using the solve.QP function to do portfolio optimization.  I
> > am trying to following a textbook example and need help converting the
> > problem into the format required by solve.QP.  Below is my sample code
> > if anyone is willing to go through it.  This problem will not solve
> > because it is not set up properly.  I hope I included enough details
> > for someone to deciper it.  Or does anyone have a good example they
> > can send me?
> 
> You can look at the man page, code and example of the function
> portfolio.optim() in package tseries which does portfolio optimization
> based on solve.QP from quadprog.
> 
> hth,
> Z
> 
> > Thanks so much for any hints and suggestions, Roger.
> >
> >
> >
> > library(quadprog, lib.loc="C:\\Program Files\\R\\tools")
> > library(MASS, lib.loc="C:\\Program Files\\R\\tools")
> > n<-100
> > m<-200
> > rho<-0.7
> > sigma<-0.2
> > mu<-0.1
> > Cov <- matrix(rho*sigma*sigma, ncol=n, nrow=n)
> > diag(Cov) <- rep(sigma*sigma, n)
> > S <- 1+matrix(mvrnorm(m, rep(mu, n), Sigma=Cov), ncol=n)
> >
> > #The problem is formulated as minimize t(b) Cov b
> > #subject to cLo <= A <= cUp
> > #and bLo=0 <= w <= 1=bUp
> >
> > Cov <- var(S)
> > mu <- apply(S, 2, mean)
> > mu.target <- 0.1
> > #subject to cLo <= A <= cUp and bLo=0 <= b <= 1=bUp
> > A <- rbind(1,mu)
> > cLo <- c(1, mu.target)
> > cUp <- c(1, Inf)
> > bLo <- rep(0, n)
> > bUp <- rep(1, n)
> >
> > #I convert [cLo <= A <= cUp] to Amat >= bvec and [bLo=0 <= w #<=1=bUp]
> > #to
> > Amat <- rbind(-1, 1, -mu, mu)
> > dim(bLo) <- c(n,1)
> > dim(bUp) <- c(n,1)
> > bvec <- rbind(-1, 1, mu.target, Inf, bLo, -bUp)
> > zMat <- matrix(rep(0,2*n*n),ncol=n, nrow=n*2)
> > zMat[,1] <- c(rep(1,n), rep(-1,n))
> > Amat <- t(rbind(Amat, zMat))
> >
> > #So I set Dmat=Cov and set dvec=0
> > Dmat=Cov
> > dvec=rep(0, nrow(Amat))
> >
> > #The first two rows of Amat should be equality constraints (so weights
> > #sum to 1)
> > meq <- 2
> >
> > sol <- solve.QP(Dmat=Dmat, dvec=dvec, Amat=Amat, bvec=bvec, meq)
> > sol
> > 
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