These different solutions incorporate different ways
of ignoring any serial dependence in your data. Perhaps
that is not problematic for stock market returns, but
I don't recall anyone in this thread addressing the
point, which was made earlier. But in essence whenever
data are time series, independence is hardly the default
expectation.
Harold Jeffreys in his "Theory of probability" (which
should have been called something like "Bayesian data
analysis", except that would have been doubly anachronistic
in 1939) has a section on human weaknesses that make
statistics difficult. One is wishful thinking. In this
case, preferring to believe that there might not be
a problem doesn't make it go away.
Nick
[email protected]
Thomas Erdmann
Thanks again to all for the ongoing suggestions.
<snip>
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