[R-SIG-Finance] fPortfolio question: is it possible to optimize aportfolio when you've got missing (returns) data for a subsetof your total assets?

[King, David]

See 'Covariance Misspecification in Asset Allocation' by Peterson and
Grier (FAJ 2006, Vol 62 No.4) and the references given in the paper
especially the work by Stambaugh.

Bernd Scherer's book 'Portfolio Construction and Risk Budgeting' also
contains useful information on this topic.

David


-----Original Message-----
From: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of Jorgy
Porgee
Sent: 04 February 2010 12:45
To: r-sig-finance at stat.math.ethz.ch
Subject: [R-SIG-Finance] fPortfolio question: is it possible to optimize
aportfolio when you've got missing (returns) data for a subsetof your
total assets?

Good day all,

I'm trying to create a MV portfolio using a bunch of stock returns.
However, the length of the historic data is not uniform (some stocks
have 12 month historics say while the bulk have 24 which is what I'm
interested in).

Is there a way of creating a portfolio (so far I've tried a
feasiblePortfolio()) without dropping the subset with short histories?

So far I get this error:

> setWeights(ewSpec)<-rep(1/nAssets,times=nAssets)
> ewPortfolio<-feasiblePortfolio(
	data = asset.returns,
	spec = ewSpec,
	constraints = "LongOnly"
	)

Error in quantile.default(returns, alpha, type = 1) :
  missing values and NaN's not allowed if 'na.rm' is FALSE

Thanking you in advance,

Jorgy.

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