Covariance matrix for financial time series object
cov is not recommended. Use timetable instead. For more information, see Convert Financial Time Series Objects fints to Timetables.
cov(X) cov(X,Y)
| Financial time series object. |
| Financial time series object. |
cov for financial time series objects is based on the MATLAB®
cov function. See cov.
If X is a financial time series object with one series,
cov(X) returns the variance. For a financial time series object
containing multiple series, where each row is an observation, and each series a
variable, cov(X) is the covariance matrix.
diag(cov(X)) is a vector of variances for each series and
sqrt(diag(cov(X))) is a vector of standard deviations.
cov(X, Y), where X and Y are
financial time series objects with the same number of elements, is equivalent to
cov([X(:) Y(:)]).
cov(X) or cov(X, Y) normalizes by
(N -1) if N >
1, where N is the number of observations. This
makes cov(X) the best unbiased estimate of the covariance matrix if
the observations are from a normal distribution. For N =
1, cov normalizes by
N.
cov(X, 1) or cov(X, Y, 1) normalizes by
N and produces the second moment matrix of the observations about
their mean. cov(X, Y, 0) is the same as cov(X, Y)
and cov(X, 0) is the same as cov(X). The mean is
removed from each column before calculating the result.