fPortfolio question: is it possible to optimizeaportfolio when you've got missing (returns) data for asubsetof your total assets?

Well, an even easier approach would be to use a simple factor model, like
Sharpe's single index model, to construct the return covariance matrix for
the assets. You can estimate the factor model on the available histories for
each stock and then construct the covariance matrix from the factor model
estimates (e.g. betas, factor covariances and residual variances). While
this doesn't use the "in-fill" approach of Stambaugh, it is certainly easier
to implement and would provide a good starting point.

Eric Zivot                  			
Professor and Gary Waterman Distinguished Scholar
Department of Economics
Adjunct Professor of Finance
Adjunct Professor of Statistics
Box 353330                  email:  ezivot at u.washington.edu
University of Washington    phone:  206-543-6715
Seattle, WA 98195-3330
www:  http://faculty.washington.edu/ezivot


-----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
david.jessop at ubs.com
Sent: Thursday, February 04, 2010 7:46 AM
To: David.King at schroders.com; jorgy.porgee at gmail.com;
r-sig-finance at stat.math.ethz.ch
Subject: Re: [R-SIG-Finance] fPortfolio question: is it possible to
optimizeaportfolio when you've got missing (returns) data for asubsetof your
total assets?

Hi

Also, look for papers by Gramacy [Gramacy, R. B., Lee, J. H., and Silva,
R. (2008). "On estimating covariances between
many assets with histories of highly variable length." Tech. Rep.
0710.5837, arXiv. Url:http://arxiv.org/abs/0710.5837. ] who has extended
the Stambaugh approach.  And he's even been nice enough to produce an R
library to do what he talks about.

Regards

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 King,
David
Sent: 04 February 2010 13:10
To: Jorgy Porgee; r-sig-finance at stat.math.ethz.ch
Subject: Re: [R-SIG-Finance] fPortfolio question: is it possible to
optimizeaportfolio when you've got missing (returns) data for asubsetof
your total assets?


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.