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I ran a linear regression with one dependent and one explanatory variable. The data covers log returns of an index and log returns of a stock (natural logarithm). log return of stock = Alpha + Beta + log return of index + error

The p value for the Beta estimate is <2e-16. I googled the meaning of this number, which means that the p value is extremely close to zero, but it does not equal to zero.

Now I am confused, since values below 0.01 show significant results, but what if the p value is practically zero? Does it mean that the regression provides a perfect fit?

gung - Reinstate Monica
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    It certainly *doesn't* represent a perfect fit. WIth a large enough sample even the noisiest and weakest of sample relationships can have extremely small p-values. – Glen_b Sep 25 '17 at 10:31
  • Please explain terms in the model incuding alpha, beta. What is log-return of index ? –  Sep 27 '17 at 06:41

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