What are forecast markets?
prediction markets are a system for predicting probability of various events and making money from accurate predictions. Probably a dozen exists and is open to the public, including popular scientific predictions, tradeSports, Iowa Electronic Markets, Newsfutares, Bet2Give, Hollywood Stock Exchange, Simexchange, Intrade and Betfair. In general, they are concentrated around the general area of predictions such as politics, films and films, technology and futurism. Other names for prediction markets include decision markets, information markets, futures for the idea, event derivatives and virtual markets. However, many prediction markets use imaginary money rather than real money. Nevertheless, evidence shows that prediction markets using fictiona money can be successful in performing accurate predictions. One study compared the NFL forecasts for the whole season using an imaginary prediction market based on money and real money prediction and found that it was not predictive than the first.
prediction markets have a significant history that stretches back to the 1940s, when people bet on which politicians win the campaign. However, only in 1990, when Robin Hanson's first market was created in the Xanadu Software Company. This prediction market was used to insert scientific controversies of that time, as it is, whether the merger is cold or not. This was followed by other prediction markets at the end of the 90s and the early 1920s, when the use of the Internet expanded and the idea of the prediction market became more known.
Today there is a contraventy about the efficacy of prediction markets, or even whether they are ethical or not. For example, Robin Hanson, aforementioned earlier, tried to set up a prediction market by public funding, shortly after 9/11 to assess the likelihood of terrorist attacks. This idea was quickly abolished by people who saw the whole idea as unethical. AcademEmii published posts that claim that prediction markets are only useful if the probability of an event is almost 1 or 0. For prediction markets to prove their effectiveness in the real world wider audience, they will have to make better demonstrations of their predictive strength.