I am a little bit stuck with my dissertation thesis, so help will be greatly appreciated. I am trying to analyze the performance of different mutual funds, which I have classified according to investment style using a holdings-based analysis. My sample period of reference ranges from 2007 to 2018, with quarterly observations. I have also retrieved the quarterly returns for all these mutual funds, over the sample period.

Now I would like to aggregate all the funds which have a similar investment strategy, and compare the performance of these different groups over the period, eventually demonstrating whether the difference in performance is statistically significant or not.

Do you have any suggestion on how should I aggregate the returns? And as for the comparison of performance, should I simply plot the returns and run a regression and then look at the coefficients?

Thanks in advance

  • $\begingroup$ Probably just equally weight the averages. (Cap weights in equity indices reflect the impact larger companies have over smaller ones. I doubt that applies to mutual funds.) An alternative is to find an existing market index that the funds claim to target, and then just use that. $\endgroup$ – chrisaycock Jun 25 at 15:48

My suggestion is the following:

  1. Build a value-weighted and equally weighted portfolio of mutual fund returns based on their style.
  2. Regress the returns on all portfolios against a factor model (ideally 4-Factor model + factors known to explain mutual fund performance)
  3. Se if $\alpha$'s are different from zero.
  4. Test for differences in $\alpha$'s (performance)
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  • $\begingroup$ Hi phdstudent, Now that I have read your comment, I am thinking about building different market cap weighted indexes using the returns of the funds that are classified in each decile of the x score, for a total of 10 indexes. Does it matter if I have fewer funds in an index? In total, I have 50 funds in my sample, so maybe in a given decile I may have just one fund. Would this still be correct? $\endgroup$ – Luigi D'Amato Jun 26 at 17:50

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