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Correlation coefficient
### Correlation coefficient – **Symbol:** `rho_(S1,S2)`, abbreviated: `rho_(1,2)`
– `rho` is a Greek letter pronounced רו. **The correlation coefficient** is a statistical tool that can be used to measure the strength of the common variance between 2 stocks. If the **correlation coefficient** of the pair of stocks S 1 and S 2 is 0.8, and the correlation coefficient of the pair of stocks S 3 and S 4 is 0.4, then the strength of the relationship (i.e., how well variable 1 allows us to predict variable 2) in the pair S 1 and S 2 is 2 times greater than that of the pair S 3 and S 4 .
The formula for calculating the **correlation coefficient** is as follows:
`rho_(1,2) = Sigma_(1,2) / ([Sigma_1] *[Sigma_2] )` #### Legend – `S_1` – One share.
– `S_2` – Second share.
– `Sigma_(1,2)` – the common variance of stocks S 1 and S 2 .
– `[Sigma_1] ` – Standard deviation of S 1 .
– `[Sigma_2] ` – Standard deviation of S 2 . The correlation coefficient can only accept results between (-1) and (+1). Despite the simplicity of the formula for calculating the correlation coefficient, the statistical knowledge required to understand it is beyond what is required of MBA graduates. Just use the tool. ### Example: What is the correlation coefficient between stocks S 5 and S 6 from the previous calculation example?
– `SigmaS_5 = 0.024`
– `σs_6 = 0.032`
– `σ_5,6 = 7.68 * 10^-4` and therefore: `rho_(5,6) = Sigma_(5,6) / (SigmaS_5 * SigmaS_6) = (7.68 * 10^-4) / (0.024 * 0.032)`