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

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

Patrick Burns-2
(missed the list on this one)

-------- Original Message --------
Subject: Re: [R-SIG-Finance] fPortfolio question: is it possible to
optimizeaportfolio when you've got missing (returns) data for asubsetof
your total assets?
Date: Thu, 04 Feb 2010 16:37:48 +0000
From: Patrick Burns <[hidden email]>
To: [hidden email]

Thanks for pointing out 'monomvn', I'd previously
missed it.

 From a quick perusal of the paper I didn't see an
answer to the following question.  When there are
missing values, the covariance estimates are going
to be shrunk towards something (at least at the
moment I can't see how that can't be the case).
How you want the shrinkage to happen will depend on
what you are doing.  Optimizing long-short may be
different than optimizing long-only.  Optimizing
long-only relative to a benchmark can be different
from long-only independent of the benchmark.  I've
seen significant differences in the case of estimating
the variance with a statistical factor model.

Has there been any study of this estimator with missing
values for different types of portfolios?


On 04/02/2010 15:46, [hidden email] wrote:

> 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: [hidden email]
> [mailto:[hidden email]] On Behalf Of King,
> David
> Sent: 04 February 2010 13:10
> To: Jorgy Porgee; [hidden email]
> 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: [hidden email]
> [mailto:[hidden email]] On Behalf Of Jorgy
> Porgee
> Sent: 04 February 2010 12:45
> To: [hidden email]
> 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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--
Patrick Burns
[hidden email]
http://www.burns-stat.com

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