A correlation is a statistical measure of the relationship between two variables. The measure is best used in variables that demonstrate a linear relationship between each other. The correlation coefficient is a value that indicates the strength of the relationship between variables. The coefficient can take any values from -1 to 1.
The interpretations of the values are: - -1: Perfect negative correlation. The variables tend to move in opposite directions (i.e., when one variable increases, the other variable decreases).
- 0: No correlation. The variables do not have a relationship with each other.
- 1: Perfect positive correlation. The variables tend to move in the same direction (i.e., when one variable increases, the other variable also increases).
In the above correlation matrix we prepared using our data set of over 50 key fundamental financial metrics, we ran the correlations between a few key fundamental financial metrics to understand their impact on Earnings Per Share. We chose 3D Systems Corp in our analysis. As you can see, over the last 10 years, Earnings Per Share has a positive correlation between Cash Flow Liquidity, Gross Margin, and Profit Margin and a negative correlation between Debt Ratio, Operating Expense as a % of Sales, and Total Asset Turnover. Since each company will have its own correlation matrix, it's critical for portfolio and investment managers to incorporate these profiles into their asset allocation and risk mitigation strategies. In order to calculate the correlation coefficient you must undertake the following steps: - Obtain a data sample with the values of x-variable and y-variable.
- Calculate the means (averages)
*x̅*for the x-variable and*ȳ*for the y-variable. - For the x-variable, subtract the mean from each value of the x-variable (let’s call this new variable “a”). Do the same for the y-variable (let’s call this variable “b”).
- Multiply each a-value by the corresponding b-value and find the sum of these multiplications (the final value is the numerator in the formula).
- Square each a-value and calculate the sum of the result
- Find the square root of the value obtained in the previous step (this is the denominator in the formula).
- Divide the value obtained in
*step 4*by the value obtained in*step 7*.
As you can see, the manual calculation of the correlation coefficient is an extremely tedious process, especially if the data sample is large. However, with SEC Reporting Analytics data set, now available Snowflake Data Marketplace, you don't need to spend hundreds of thousands of dollars and several years to develop quality quant financial training data. Your current team of data scientists, analytics managers, and portfolio managers can begin developing their own custom correlation, regression, and predictive analysis TODAY! We also provide ad-hoc correlation requests for individual tickers or a basket of tickers. Contact [email protected] with your requests. We look forward to hearing from you! Credit: SEC Reporting Analytics Corporate Finance Institute
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