[R] FW: Frontier efficient using black litterman model In R

[Ava Yang]

Hi Mukesh,

Glad to see someone using BLCOP.

You didn't provide a reproducible example so I assume you got a result list complete from optimalPortfolios.fPort() and wanted to obtain details of all the 10 simulations.

Short answer to your question: the function only renders the optimal value which is the mean of simulations. It is a wrapper of efficientPortfolio functions(minriskPortfolio in your example) from package fPortfolio. I believe looking deep at the source of optimalPortfolios.fPort, structure of result and slot details would help.

Best regards,

Ava

-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of mukesh surywanshi
Sent: 03 March 2015 06:34
To: r-help at r-project.org
Subject: [R] Frontier efficient using black litterman model In R

Hi
I'm working on getting frontier efficient plot using Black Litterman model.

I have used Blcop package and its function

optimalPortfolio.optim()

using this i have got optimal risk and return with weights

If i want to get 10 portfolio risk and return with corresponding weights,,, how to do it>?
 can anyone help me....


my code goes like this
posterior <- posteriorEst(views, tau = 0.025, meanret, covar)

cons <- c("minW[1:numtk] = rep(0, times = numtk)", "maxW[1:numtk] = rep(0.50, times = numtk)","minsumW[1:numtk] = 0","maxsumW[1:numtk] = 1") #"listF = list(lowerExtension, upperExtension)")

res1<-optimalPortfolios.fPort(posterior,
spec=portfolioSpec(),constraints=cons,optimizer = "minriskPortfolio",numSimulations  = 10)



Thanks
MUKESH

	[[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

--

LEGAL NOTICE\ \ This message is intended for the use of ...{{dropped:18}}