Covariance

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Related to covariances: correlation

Covariance

A statistical measure of the degree to which random variables move together. A positive covariance implies that one variable is above (below) its mean value when the other variable is above (below) its mean value.

Covariance

The degree to which two variables are correlated. That is, covariance is the measure of how much two variables are related to one another. It is important in security analysis to determine how much or how little price movements in two companies or industries are connected.

covariance

A statistical measure of the extent to which two variables move together. Covariance is used by financial analysts to determine the degree to which return on two securities is related. In general, a high covariance indicates similar movements and lack of diversification. Compare variance. See also risk.
References in periodicals archive ?
Keywords: Markov source, variance, covariance, independence, Hamming weight, Matrix-Tree Theorem, transducer, central limit theorem
The means and variances used to generate the covariance matrices and; therefore, the multivariate random samples for the calculations of the type I error and the power of the LRT for the independence between two groups of variables belong to the groups of adult plants and the production of the hybrid Lyra (Table 1).
i][beta] and variance and covariance matrixes, according as Equation 2:
Random effects included direct and maternal additive genetic effects, maternal permanent environmental effects with direct maternal genetic covariance and random residual effects.
Because of Hirvonen function is commonly used in geodetic studies, this function was chosen for computation of experimental covariances in this study.
The risk-free rate of return on the risk-free asset is r, an n x 1 vector of the expected excess rates of return is R - r, and the n x n non-singular covariance matrix of risky assets' rates of return is [OMEGA].
Remark 1: The GLR test statistic only uses the asymptotic covariance matrix under [H.
For detecting the quantity of changes between the same model elements of the same speakers we compare the training and test covariance matrices of the same speakers and calculate matrix of distinctions
If the covariance matrix of the vector meets the alternative assumption (15), the following applies
This decomposition implies that family income changes can arise directly from one of the five sources or from the covariances between the income sources.
The Patterns of Covariances between Growth Parameters and the Corresponding Patterns of Constraints upon the Magnitude of Variation of Functional Parameters
In that type of representation, one loses the inter-temporal variation of covariances between portfolio returns and state variables.