L.S.:
I have the following problem:
My data are the returns on a quarterly basis of leveraged buyout funds in
the USA from 1989 to 1999 (40 quarters). I have bought this data in two
groups with in one group funds smaller (in terms of capital under
management) then a certain size; in the other funds larger then that certain
size. This way I can test whether the returns of the smaller funds behave
differently from those of the larger funds.
My hypothesis is that the smaller funds have higher returns. Not just that,
even better for their investors, they also have a lower risk level (standard
deviation of returns).
There are way more smaller buyout firms then there are large ones. The
returns of the smaller funds are the combined results of about 150 firms
(from 80 in 1989 to 225 in 1999); the results of the large buyout firms are
the combined results of 8 in 1989 to 63 in 1999. Since I only have the
returns of the combined funds as observations I do only have N=40. One can
imagine that the standard deviation of returns is a lot lower for the
smaller funds this way in the first place because it is comprised of less
funds in the first place... [Standard deviaton is about 4 vs. 8] .
How can I approach this problem: correcting for the larger number the
data is comprised of for smaller funds (or: correcting for the smaller
numbers the data is comprised of for the larger funds) if I want to test for
return level & standard deviation?
Help greatly appreciated!!
Edzo Wisman
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