Appendix 22.1: Covariance Matrix Estimation
Consider the simplest case with two return series 
for 
and 
for 
where 
. Truncation to S would imply that means be equal to their maximum likelihood estimates:
(22.1) 
Here, 
and 
are the sample MLE for the truncated sample of size S. Similarly, the MLE covariance matrix based upon S is equal to:
(22.2) 
where 
are scalars. The parameters 
and are typically ...
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