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The correlation coefficient can be understood as an indicator of two things. The first is whether or not the two variables in question typically move in the same direction at the same time. If they do, the correlation coefficient is positive. If not, it is negative. The second thing the correlation coefficient can tell you is how similar these movements are. A correlation coefficient close of 1 or -1 represents perfect positive correlation or perfect negative correlation, respectively.  Correlation coefficients always vary between 1 and -1. A result of 0 indicates that there is no correlation.  So, for example, the example result of 0.809 from the other part of this article would mean that stocks X and Y are highly correlated. The two securities experience price movements in the same direction and usually in roughly the same magnitude. The primary use of stock correlation coefficients is in the preparation of balanced securities portfolios. Stocks or other assets within a portfolio can be assessed against others in the same portfolio to determine the correlation coefficient between them. The goal is to place stocks with low or negative correlations in the same portfolio. Thus, when the price of the first stock moves, the second will likely move oppositely or independently of the first. The result of these actions is effective portfolio diversification. This practice reduces "unsystematic risk," which is risk inherent to individual securities. The correlation coefficient is also frequently used to assess relationships between other data sets, such as mutual fund returns, Exchange Traded Fund (ETF) returns, and market indexes. Correlations coefficients can be calculated between these data sets and stock returns to diversify a portfolio or to figure out how a stock's price moves in relation to other market shifts. This can be useful for predicting the change in a stock's price that would occur in the event of another change in the market. For example, the stock price of a gold mining company might be positively related to the price of gold (with a high, positive correlation coefficient). If the price of gold is expected to increase, an investor would have reason to believe that the price of the company's stock will as well. of stock return data to obtain a 'scatter plot'. You can use a spreadsheet program to plot the dates and returns of your stocks. This makes it easier to note the properties of the data. Also, using spreadsheet software, you can plot a best fit line. The best fit line to the data is called the regression line.  On Excel, you can add this line by clicking "Chart" and then "Add Trendline." The program will then calculate a trend line based on your data.  The correlation coefficient is a measure of how closely the two stock returns fit the regression line. That is, how closely the return values satisfy a linear relation such as Y = βX + α for some constants α and β.

Summary:
Understand your correlation coefficient result. Reduce risk in your portfolio. Expand your analysis to other assets. Plot the pairs