# Correlation Coefficient

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## Definition of 'Correlation Coefficient'

A correlation coefficient is a statistical measure of the strength of the linear relationship between two variables. It is a number between -1 and 1, where:

-1 indicates a perfect negative correlation, meaning that as one variable increases, the other decreases.

0 indicates no correlation, meaning that there is no clear relationship between the two variables.

1 indicates a perfect positive correlation, meaning that as one variable increases, the other also increases.

Correlation coefficients are used in finance to measure the relationship between different financial assets. For example, a correlation coefficient of 0.7 between the price of two stocks would indicate that the two stocks tend to move in the same direction. This information can be used by investors to make informed decisions about their portfolios.

Here are some points to consider about correlation coefficients:

Correlation coefficients are only a measure of linear relationships. This means that they may not be able to capture all of the relationships between two variables.

The magnitude of a correlation coefficient does not necessarily indicate the significance of the relationship. A correlation coefficient of 0.5 may be significant if the sample size is large, but it may not be significant if the sample size is small.

Correlation coefficients can be used to calculate the probability that two variables are related. However, it is important to note that correlation does not equal causation. Just because two variables are correlated does not mean that one variable causes the other.

-1 indicates a perfect negative correlation, meaning that as one variable increases, the other decreases.

0 indicates no correlation, meaning that there is no clear relationship between the two variables.

1 indicates a perfect positive correlation, meaning that as one variable increases, the other also increases.

Correlation coefficients are used in finance to measure the relationship between different financial assets. For example, a correlation coefficient of 0.7 between the price of two stocks would indicate that the two stocks tend to move in the same direction. This information can be used by investors to make informed decisions about their portfolios.

Here are some points to consider about correlation coefficients:

Correlation coefficients are only a measure of linear relationships. This means that they may not be able to capture all of the relationships between two variables.

The magnitude of a correlation coefficient does not necessarily indicate the significance of the relationship. A correlation coefficient of 0.5 may be significant if the sample size is large, but it may not be significant if the sample size is small.

Correlation coefficients can be used to calculate the probability that two variables are related. However, it is important to note that correlation does not equal causation. Just because two variables are correlated does not mean that one variable causes the other.

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Copyright © 2004-2023, MyPivots. All rights reserved.