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INSIDER TRADING
AND MEAN-VARIANCE
ANALYSIS
The paper contributes to the
literature by developing and testing a
model of insider trading behavior around
the release of annual earnings
information. The study hypothesizes that
utility maximizing insiders with private
information concerning annual earnings
will increase their trading activity
several weeks prior to the public release
of earnings, but will refrain from trading
in the period immediately preceding the
earnings release. The empirical analysis,
using an event study methodology, is
generally consistent with the predicted
behavior.
The study attempts to shed
additional light on the issue of the costs
and benefits of using the mean-variance
criterion as opposed to stochastic dominance
criteria for investment decisions. Relevant
probabilities which facilitate measurement
of these costs and benefits are identified.
The mean-variance criterion is shown to be
useful to some extent in identifying
potentially optimal portfolios. However, it
is shown that the informationally less
demanding mean-variance criterion admits two
types of errors: (i) including portfolios
that no expected utility maximizing risk
averters would choose, and (ii) excluding
portfolios which some risk averters would
find optimal. The empirical investigation
also indicates that although the composition
of the efficient sets appears to be unstable
over time, the relationships between the
efficient sets are persistent over time.
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