[gov3009-l] Paper Available: Internet Stocks and Market Classification

Anders Schwartz Corr corr@fas.harvard.edu
Tue, 5 Nov 2002 17:55:22 -0500 (EST)

Paper now available at:


Shrewd, Crude, or Simply Deluded? Market Classification and the Internet
Stock Phenomenon. Ezra Zuckerman (MIT, Sloan School of Management)

Wednesday November 6 at noon
Center for Basic Research in the Social Sciences
34 Kirkland Street, Room 22
Lunch will be served.


We analyze comovement among Internet and other categories of stocks during
the late 1990s and 2000 in an effort to assess the sophistication of
stock-market valuation.  Prominent accounts of the Internet stock
phenomenon suggest that the prices of these stocks were determined by
simplistic thinking.  In particular, investors were not discriminating as
they crudely grouped all Internet stocks into an undifferentiated and
highly attractive investment category.  We find that, in fact, comovement
among Internet stocks was high throughout much of this period but did not
reach the very high levels assumed by prevailing accounts. In addition, we
describe two additional patterns that are problematic for such
interpretations.  First, comovement is less characteristic of price
increases than of price drops.  Second, Internet stocks exhibited moderate
to high period-to-period consistency in the manner by which category
members were distinguished by investors.  Together, our evidence supports
our view that, rather than being anomalous, the Internet stock phenomenon
was symptomatic of the general way by which equity prices are determined:
valuation is driven by prevailing theories of value, which are reasonable
but quite fallible.  This view has important implications for how scholars
and managers understand and react to stock market dynamics.

The paper will be posted as soon as it becomes available on the workshop
website, www.courses.fas.harvard.edu/~gov3009/fall02/

The Research Workshop in Applied Statistics is a forum for graduate
students, faculty, and visiting scholars to present and discuss
statistical innovations and applications in the social sciences. For more
information, contact corr@fas.harvard.edu.