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Maybe I'm not providing a full information. But if you're asking about importance of covariance in trading, then before investing you should assess if your stocks are codependent.

All investors try to diversify a portfolio and minimize risks. and covariance can show if two stocks are exposed to the same risk.

Now it's easily calculated, there're different services. Actually, for better understanding just read Investopedia really.

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Covariance is important because it measures the relationship between two variables. It indicates the direction and strength of the relationship between the variables. Covariance can help in understanding and predicting the behavior of variables and is widely used in statistics, finance, and economics.

Q: Why is covariance important?

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variance - covariance - how to calculate and its uses

The covariance between two variables is simply the average product of the values of two variables that have been expressed as deviations from their respective means. ------------------------------------------------------------------------------------------------- A worked example may be referenced at: http://math.info/Statistics/Covariance

One can find information on the covariance matrix on the Wikipedia website where there is much information about the mathematics involved. One can also find information on Mathworks.

look in a maths dictionary

100 x (standard deviation/mean)

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variance - covariance - how to calculate and its uses

Covariance - 2011 was released on: USA: 20 September 2011

) Distinguish clearly between analysis of variance and analysis of covariance.

[N*(N-1)]/2 N=1700 (1700*1699)/2 = 1,444,150 Covariance

The covariance between two variables is simply the average product of the values of two variables that have been expressed as deviations from their respective means. ------------------------------------------------------------------------------------------------- A worked example may be referenced at: http://math.info/Statistics/Covariance

A mix of linear regression and analysis of variance. analysis of covariance is responsible for intergroup variance when analysis of variance is performed.

Covariance: An Overview. Variance refers to the spread of a data set around its mean value, while a covariance refers to the measure of the directional relationship between two random variables.

The cast of Covariance - 2011 includes: David Razowsky as Russell Gains Dawn Westlake as Genevieve Pace

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When you carrying out multivariate analyses.

One can find information on the covariance matrix on the Wikipedia website where there is much information about the mathematics involved. One can also find information on Mathworks.

ANCOVA is an acronymical abbreviation for analysis of covariance.