Biology Reference
In-Depth Information
juice futures prices demonstrated that the changes in the price of futures
seemed to precede, and thus anticipate, the weather forecasts released by the
National Weather Service (Roll 1984). Apparently, commodity traders with
large sums of money at stake effectively seek out and use information that is
not yet available to, or not yet used by, the National Weather Service.
8.3 Prediction Markets
In recent years, markets in more “unusual” commodities have been devel-
oped solely for their utility in predicting future events. These markets are
designed exclusively to exploit the information contained in the prices of the
financial instruments, or contracts, traded. No tangible “commodity,” such
as a crop or raw material, is attached to the contracts that participants buy
and sell. They are based instead on the outcome of some future event. We
call these markets prediction markets rather than futures markets; this name
implies their intended use and helps to distinguish them from traditional
financial futures markets. They have also been called decision markets, event
markets, and information markets.
One can think of prediction markets as specialized futures markets in
which artificial financial instruments are traded. The instruments (i.e., con-
tracts) are defined by the operators of the market to have a value to be deter-
mined by the outcome of the event of interest. Participating traders in the
market are experts with information regarding that event. They are moti-
vated to trade by the prospect of making profits. Thus, traders buy contracts
that are undervalued by the market, according to their beliefs, and sell those
which are overvalued. The prices at which these instruments trade reflect a
consensus belief about their future value, and thus can be used as a predic-
tion of the future event.
8.3.1 How Do Prediction Markets Work?
Prediction markets are effective because they aggregate the disparate and dif-
fuse information held by different participants. A simple example, patterned
after one provided by Eisenberg and Gale (Eisenberg et al. 1958), illustrates
how markets aggregate information. Suppose there are two traders and
three possible outcomes to an event: A, B, C. Only one outcome will occur
6 months from now. With no other information, each trader might regard
each outcome as equally likely to occur and thus be willing to pay the same
amount for contracts linked to those outcomes. Suppose, instead, that each
trader has access to different information. Trader 1 knows that event A will
not occur, and trader 2 knows that event B cannot occur. Each trader is still is
uncertain about the outcome. However, trader 1 believes that events B and C