I have been attempting to do a cross-sectional test of the CAPM.

To do this, i have estimated the betas of 49 industry portfolios with time-series data. And then done a cross sectional regression, where i regressed the mean excess returns on the estimated betas, with a forced intercept of 0, to get the security market line.

And i got the following result:

enter image description here

How can i test if the residuals (pricing errors) are significantly different from 0 with R?


I am trying to do what is described in this video: https://www.youtube.com/watch?v=zxTfVIWZg34 but i lack the R knowledge to actually perform the test.

  • $\begingroup$ you might consider defining acronyms and "excess returns" because not everyone is well-versed in finance theory on this site. Also, do you mean 49 observations of one portfolio? Also do you mean "excess returns" instead of "mean excess returns"? Also, you don't regress "on betas;" you regress "on" the predictors, which in this case should be (but you don't mention it) the excess returns of some index. Last, you don't test residuals; you test parameters. $\endgroup$ – Taylor Jun 10 at 23:32
  • $\begingroup$ If you regress with an intercept, calling summary() on your model object should give you a t test of the null hypothesis that the intercept term is 0. $\endgroup$ – Taylor Jun 10 at 23:34
  • $\begingroup$ I have 49 portfolios with monthly observations from 1926 till now. I have already done the time-series regression where i regress the excess returns on the excess return of the market portfolio. But now i am trying to do a cross-sectional test as described in this video: youtu.be/zxTfVIWZg34?t=414 $\endgroup$ – Lazy019 Jun 10 at 23:53
  • $\begingroup$ Oh I misunderstood then! $\endgroup$ – Taylor Jun 11 at 1:12

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