This example shows how to compute the value of the observed negative log-likelihood function for five years of daily total return data for 12 computer technology stocks, with six hardware and six software companies
load ecmtechdemo.mat
The time period for this data extends from April 19, 2000 to April 18, 2005. The sixth stock in Assets is Google (GOOG), which started trading on August 19, 2004. So, all returns before August 20, 2004 are missing and represented as NaNs. Also, Amazon (AMZN) had a few days with missing values scattered throughout the past five years.
Data, specified as an
NUMSAMPLES-by-NUMSERIES matrix
with NUMSAMPLES samples of a
NUMSERIES-dimensional random vector. Missing values are
indicated by NaNs.
Data Types: double
Mean — Maximum likelihood parameter estimates for mean of Data vector
Maximum likelihood parameter estimates for the mean of the
Data using the ECM algorithm, specified as a
NUMSERIES-by-1 column vector.
Covariance — Maximum likelihood parameter estimates for covariance of Data matrix
Maximum likelihood parameter estimates for the covariance of the
Data using the ECM algorithm, specified as a
NUMSERIES-by-NUMSERIES
matrix.
You can also select a web site from the following list:
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.