[R-SIG-Finance] [R-sig-finance] Flexible inputs fPortfolio possible?

[R@Nabble]

Following your advice,  I did the following:
 
PropEstimates<-function(x,Estmu=colMeans(x),Covar=cov(x)) list(mu=Estmu,
Sigma=Covar)
####### Efficient Frontier
Data <- as.timeSeries(MatR)
NAss=ncol(Data)
NAss
SpecDef <- portfolioSpec()
Rfree = 0.04/12 
setRiskFreeRate(SpecDef)<- Rfree
TotUni<-PropEstimates(Data,colMeans(Data),cov(Data))
TotUni 
This code results in the following (what looks like correct) results:
 
> TotUni
$mu
      . . . . 
$Sigma
      . . . .
 
However, if I then input this as follows:
 
setEstimator(SpecDef)<-TotUni
ConstrLO = "LongOnly"
frontierLO = portfolioFrontier(Data, SpecDef, ConstrLO)
 
I get the following error:
 
ERROR:  
  c("'structure(list(mu = structure(c(0.0025, 0.00369565217391304, ' is not
a function, character or symbol", "'0.00271739130434783,
0.00347826086956522, 0.00858695652173913, ' is not a function, character or
symbol", "'0.00119565217391304, 0.00141304347826087, -0.00282608695652174, '
is not a function, character or symbol", "'0.0101086956521739,
0.00315217391304348, 0.0197826086956522, ' is not a function, character or
symbol", "'0.0141304347826087), .Names = c(\"FTSE.All.Share\",
\"FTSE.All.Stock.Gilts\", ' is not a function, character or symbol", 

Trying to correct it by literally applying your code, and using:

PropEstimates<-function(x, spec = NULL, ...) list(mu = colMeans(x), Sigma =
cov(x))
TotUni<-PropEstimates(Data,colMeans(Data),cov(Data))
setEstimator(SpecDef)<-"TotUni" 

I get this error:
 
ERROR:  
  variable "TotUni" of mode "function" was not found

In fact, even the "old" way of doing things, for example by leaving out any
setEstimator, results in:
 
ERROR:  
  variable "covEstimator" of mode "function" was not found
 
Is this because I'm still using 2.6.2 ???

Thx for any further insights/guidance,
 
R at N




Yohan Chalabi wrote:
> 
>>>>> "R" == "R at Nabble" <vlanschot at yahoo.com>
>>>>> on Tue, 27 May 2008 04:15:15 -0700 (PDT)
> 
> 
>    R> Hi,
>    R> 
>    R> Is it possible yet to allow pre-specified mean-return and/or
>    R> covar-matrices
>    R> in fPortfolio? If so, where can I find instructions to
>    R> achieve this? I
>    R> remember reading somewhere that this would eventually become
>    R> available.
>    R> 
>    R> Thx,
>    R> 
>    R> R at N
> 
> Do you want to define your own estimators of the covariance matrix?
> 
> You can do it with the dev-version of fPortfolio available at r-forge.
> 
> a quick example :
> 
> ##################
> library(fPortfolio)
> # only with development version of fPortfolio available on R-Forge
> 
> # now you can define your own estimator which must returns a list with a
> # named list, with at least the following two entries '\$mu' and
> # '\$Sigma', which represent estimators for the mean and covariance,
> # respectively.
> myEstimator <- 
>     function(x, spec = NULL, ...) list(mu = colMeans(x), Sigma = cov(x))
> 
> Spec <- portfolioSpec() # default portfolio specification  
> setEstimator(Spec) <- "myEstimator" # new estimator
> Spec
> 
> # Load Data and Convert to timeSeries Object:
> Data = as.timeSeries(data(smallcap.ts))
> Data = Data[, c("BKE", "GG", "GYMB", "KRON")]
> Data
> 
> ## Compute properties of Efficient Portfolio
> frontier <- portfolioFrontier(Data, Spec, "LongOnly")
> plot(frontier)
> 
> ####################
> 
> hope this helps,
> Yohan
> 
> -- 
> PhD student
> Swiss Federal Institute of Technology
> Zurich
> 
> www.ethz.ch
> www.rmetrics.org
> 
> NOTE:
> Rmetrics Workshop: http://www.rmetrics.org/meielisalp.htm
> June 29th - July 3rd Meielisalp, Lake Thune, Switzerland
> 
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