Thanks to Patrick for your great suggestions and I will try the package to
see if it really works for me.

2011/9/19 Patrick Burns <patrick@burns-stat.com>

> There are two functions in the BurStFin
> package ('factor.model.stat' and 'var.shrink.eqcor')
> that will create variance matrix estimates
> when there are missing values in the return
> matrix.
>
> The second of those gives Ledoit-Wolf estimates,
> and is probably going to give the more useful
> results.
>
> I believe that the best way to handle missing values
> for these estimates is still an open research question.
> The functions handle missing values, no claim that
> they do it optimally.
>
> You can get the package via:
>
> install.packages('BurStFin', repos='http://www.burns-stat.**com/R<http://www.burns-stat.com/R>
> ')
>
> As for means: historical means are in general not
> of much use, so it is unlikely that it will matter
> how you estimate them.
>
>
>
> On 19/09/2011 08:26, ShyhWeir Tzang wrote:
>
>> Dear all:
>>
>> I have a portfolio of about 50 stocks of which about 10~15 stocks with
>> unequal lengths. That means they have shorter historical return series
>> than
>> others. How may I estimate the covariance matrix and mean of the stocks?
>> Is
>> the Stambaugh (1997) ("Analyzing investments whose histories differ in
>> length") method still valid for individual stocks instead of funds? Is
>> there
>> any better way or more efficient way to estimate their mean and covariance
>> matrix? Any help or suggestion is highly appreciated.
>>
>> --
>>
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>>
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>> should go.
>>
>>
> --
> Patrick Burns
> patrick@burns-stat.com
> http://www.burns-stat.com
> http://www.portfolioprobe.com/**blog <http://www.portfolioprobe.com/blog>
> twitter: @portfolioprobe
>



-- 
Shyh-Weir Tzang
Finance Department
Asia University
Tel: 04-2332-3456#48055
Mobile: 0929125845/0973830823

臧仕維
亞洲大學財務金融系
電話：04-2332-3456#48055
手機：0929125845/0973830823
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