How this synthesis works depends on how the market is designed, and on the kind of
individual and aggregate behavior that results. Nor are such issues restricted to markets
for financial assets such as stocks. Recent work, for example, has explored the design of prediction markets that use a market mechanism to provide predictions of future events such
as the outcomes of elections. Here, participants in the market purchase assets that pay a
fixed amount if a certain event takes place. In this way, the price of the asset reflects an
aggregate estimate for the probability of the event, and such estimates have been found to
be highly accurate in a number of cases — with the market’s aggregate predictions often
outperforming the opinions of expert analysts. Figure 1.13 shows an example from the
2008 U.S. Presidential Election: the upper curve depicts the price over time for an asset
that paid $1 in the event that the Democratic Party’s nominee won the election, and the
lower curve depicts the corresponding price for the Republican Party’s nominee. Note that
the market was already functioning before the identities of these nominees were known,
and it shows a clear aggregate reaction to certain events such as the contentious end of the
Democratic primary process between Obama and Clinton (in early May) and the Republican
National Convention (in early September), both of which brought the prices for the opposing
predictions close to equality, before they diverged once and for all as the actual election
neared.