If I have 24 temporal covariance matrices (say monthly covariance matrices computed from daily returns of all the SP500 stocks), and I compute 24 betas for variables x and y for every month for past 2 years. Then,

  • What is then the best estimator of beta (e.g. equally or exponentially weighted average of these betas?
  • How can I analyse the stability/variability of the individual beta as well as the estimator of the beta?
  • By looking at these monthly betas can I make any conclusions of the relationship between x & y?

I would very much appreciate, if you have any standard references that clarify my concerns.


closed as not a real question by Peter Ellis, whuber Sep 24 '12 at 14:11

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  • $\begingroup$ Perhaps this blog post portfolioprobe.com/2011/02/08/… will be of some help. The help might be to suggest that forgetting about beta would be a good move. You don't say what you are really trying to do -- that is important information. $\endgroup$ – Patrick Burns Jan 20 '12 at 15:45
  • $\begingroup$ @PatrickBurns, thanks for the link but as you can see that the value of the beta for variable x (e.g. IBM) and y (e.g. S&P) is not stable (luckily +ve in this example but may even change the signs along with the magnitude) throughout time, I would like to find a stable beta for x and y using the betas I have for each of the 24 months. $\endgroup$ – statnoob Jan 20 '12 at 16:35
  • $\begingroup$ It seems to me that you could process your sample as panel data. $\endgroup$ – Jean-Victor Côté Jan 25 '12 at 18:42
  • $\begingroup$ I may be terribly ignorant, but what is a "beta" in this situation? $\endgroup$ – Peter Ellis Feb 25 '12 at 6:59

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