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What is Correlation?
Correlation (correlation coefficient) refers to a quantitative relationship between two variables that can be measured either on ordinal or continuous scales. Correlation does not imply causation, rather it implies an association between two variables. The strength of a correlation can be indicated by the correlation coefficient.
The correlation coefficient is a statistic that is calculated from sample data and is used to estimate the corresponding population correlation coefficient. Correlation coefficients generally take values between -1 and +1. A positive value implies a positive association between variables (i.e., high values of one variable are associated with high values of the other), while a negative value implies a negative association between variables (i.e., high values of one variable are associated with low values of the other). Thus, a coefficient of -1 means the variables are perfectly negatively related; while +1 means a perfect positive relation. A coefficient of 0 means the variables are not related at all.
For investors, knowing a correlation coefficient can be useful in the following way:
If one finds that the Stock A has a 0.85 correlation coefficient with regards to their investment portfolio, the investor can expect a pretty strong positive relationship between gains in Stock A and his/her portfolio. If the correlation coefficient were -0.85, the investor could expect to see his/her portfolio lose value when Stock A gains.
Correlation (correlation coefficient) refers to a quantitative relationship between two variables that can be measured either on ordinal or continuous scales. Correlation does not imply causation, rather it implies an association between two variables. The strength of a correlation can be indicated by the correlation coefficient.
The correlation coefficient is a statistic that is calculated from sample data and is used to estimate the corresponding population correlation coefficient. Correlation coefficients generally take values between -1 and +1. A positive value implies a positive association between variables (i.e., high values of one variable are associated with high values of the other), while a negative value implies a negative association between variables (i.e., high values of one variable are associated with low values of the other). Thus, a coefficient of -1 means the variables are perfectly negatively related; while +1 means a perfect positive relation. A coefficient of 0 means the variables are not related at all.
For investors, knowing a correlation coefficient can be useful in the following way:
If one finds that the Stock A has a 0.85 correlation coefficient with regards to their investment portfolio, the investor can expect a pretty strong positive relationship between gains in Stock A and his/her portfolio. If the correlation coefficient were -0.85, the investor could expect to see his/her portfolio lose value when Stock A gains.