  Prediction markets are powerful tools to elicit and aggregate beliefs from
strategic agents. However, in current prediction markets, agents may exhaust
the social welfare by competing to be the first to update the market. We
initiate the study of the trade-off between how quickly information is
aggregated by the market, and how much this information costs. We design
markets to aggregate timely information from strategic agents to maximize
social welfare. To this end, the market must incentivize agents to invest the
correct amount of effort to acquire information: quickly enough to be useful,
but not faster (and more expensively) than necessary. The market also must
ensure that agents report their information truthfully and on time. We consider
two settings: in the first, information is only valuable before a deadline; in
the second, the value of information decreases as time passes. We use both
theorems and simulations to demonstrate the mechanisms.
