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# What is Correlation?

## What is Correlation?

Correlation measures the strength of the linear relationship between two variables and is always between —1 and 1. It’s an extension of covariance and assists researchers in knowing the strength of the relationship for better decision making.

For example, if X2 = a + bX. If then the correlation between X 1and X 2 is 1 if b > 0, — 1 if b < 0 or 0 if b = 0. The correlation between two random variables is commonly denoted by p (or 12 to specify that this is the correlation between the components).

Correlation is a measure of linear dependence. If two variables have a strong linear relationship (i.e., they produce values that lie close to a straight line), then they have a significant correlation. If two random variables have no linear relationship, then their correlation is zero

## Example of Correlation:

$Correlation = \frac{Cov (x,y)}{\sigma x*\sigma y}$

where,
Covx,y= Covariance of x and y
x= Standard Deviation
y= Standard Deviation of y

## Why is calculating correlation important?

Correlation plays a vital role in determining the benefits of portfolio diversification. Correlation has broad applicability and assists risk professionals in making better decisions by knowing the extent (positive, negative or no correlation) between variables.

Owais Siddiqui
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