TOKEN PREDICTION MARKETS
Prediction markets are speculative markets, very similar to futures markets, which have been designed so that the prices can be interpreted as probabilities for events occurring and used to make predictions.
Put very simply, prediction markets enable users to trade shares in the outcomes of an event and in so doing to reveal the information that people have about the likelihood of an event occurring.
In a very elegant way, blockchain prediction markets use tokens to reduce uncertainty and find truths about future events. As they align truthful statements with token investments they create a way for people and groups to come to consensus about a shared conception of reality by using markets to create valid sources of information.
HOW IT WORKS
A number of blockchain based prediction markets now exist such as Augur, Stox or Gnosis. Using one of these networks anyone anywhere in the world can create a market for people to try and predict the outcome to some event, such as a sports match, an election, the weather, sales of a company, price fluctuations of commodities, the availability of almonds in Spain next year or the likelihood of a conflict occurring in central Asia at a given time.
Market makers provide initial funding for the market and for this receive some trading fees. Anyone can then buy and sell shares in the outcomes of that market.
Predictions are based on a binary event where something either will or won’t happen. The value of a bet will in most cases reflect the probability of an outcome materializing.
If you place a bet on a coin flip, the outcome will always be 50% heads, 50% tails. There are no external market conditions that will influence the outcome.
Luck plays a major role, and this is called gambling.
But prediction markets rely on the collective wisdom held by a group of people on the probability of a future event materializing. The current market price of a share is an estimate of the probability of an event actually occurring. The prices of each share add up to one dollar. So if you buy a share at even odds it will cost you 50 cents. If you end up being right, you’ll receive a dollar for that share. If you see a market price of 53 cents then it is reasonable to assume that there is a 53% chance that outcome will occur.
As an example, we can think about a market for the hiring of a new CEO of a company given just two candidates, Bob and Jane. In this market, one share for the Bob option pays you a euro if he is hired and pays you nothing otherwise. One share for Jane pays you a euro if you hold the share and she is hired, and pays zero if she is not. Now, suppose you think Jane has a chance of winning that position, how much would you be willing to pay for a Jane share? If a Jane share pays a dollar if Jane wins and she has a 70% chance of winning, then that share is worth 70 cents. You would be willing to pay up to 70 cents for such a share.
Suppose you enter this market and you find that Jane’s shares are selling for just 55 cents, well, that’s a buying opportunity. Something which you think is worth 70 cents is selling for 55, so then, you should buy the Jane option. In buying the shares, you would be pushing up their price. In this way, your predictions, your information, your opinions about which candidate is likely to win become incorporated into the price of a Jane share.
Imagine however you thought Jane had a 70% chance of winning but her shares were selling for 80 cents, then, you would want to sell Jane shares. Even if you really wanted Jane to win the position of CEO. To make more money you would sell the Jane shares and buy the Bob share. In this way we can see how prices come to reflect the market information.
The prediction market really boils down to one number and if there’s anyone in the world who thinks they would know better than this number they have direct financial incentives to trade this market and basically with every trade they make they feed the information into this market and in the end we have a better number from the market.
The outcome becomes more predictable over time. This is because the payoff depends on the accurate prediction of an outcome of an event. As a larger number of people do more market research to come to the most likely conclusion, the predicted outcome will lean more favorable to one side. Current share prices over time come to reveal information about the likelihood of an event occurring according to the information gained from the market participants.
Prediction markets are not a new invention. They are in fact centuries old and have proven their effectiveness many times.
One of the most popular current markets is the Iowa Electronic Markets. In over two decades of testing this market, in presidential elections, congressional elections, and state elections, the market prices from the Iowa Electronic Markets have turned out to be better predictors of the outcomes than have political polls.
The two key features that make them successful is that firstly, they draw upon dispersed information that is consolidated and averaged out. And secondly people have skin in the game, that is to say people are putting their own money on the line and this ensures a correspondence between what they predict and what they believe to be true.
Prediction markets work to align incentives by backing statements up with resources. They work to obtain truthful and relevant information through financial and other forms of incentives. With real money on the line, people have an incentive to think carefully when they’re investing and they have an incentive to collect, process and interpret all of the information available all over the world. The resulting market prices potentially reflect a lot of deep-seated and diverse information in a way which surveys or polling cannot.
Likewise because prediction markets rely on the collective view of many, not just one person’s research, they can efficiently aggregate a plethora of information, beliefs, and data.
These markets work on the principle of the wisdom of the crowd, which states that if you ask enough people something, their average answer is usually far more accurate than anyone expert, which creates a powerful forecasting tool.
The author James Michael Surowiecki posits that there are a number of necessary conditions for collective wisdom: independence of decision, diversity of information, decentralization of organization.
In the case of predictive markets, each participant normally has diversified information from others and makes their decision independently.
The market itself has a character of decentralization compared to expertise decisions. Because of these reasons, predictive markets are generally a valuable source to capture collective wisdom and make accurate predictions.
Equally the ability of the prediction market to aggregate information and make accurate predictions is based on the Efficient Market Hypothesis, which states that assets prices are fully reflecting all available information. For instance, existing share prices always include all the relevant related information for the stock market to make accurate predictions.
Prediction markets create a very dynamic system, as opposed to a seven-year plan or a yearly assessment, prediction markets can incorporate new information quickly and may be continuously updated.
Using a blockchain as the IT infrastructure adds additional benefits to prediction markets. By creating prediction markets on a blockchain network we can ensure that the data always remains open and accessible to all parties. It removes the possibility for the centralized authority to alter results, it can thus be trusted, is secure and if designed well blockchain prediction markets may be difficult to manipulate.
Prediction markets may be used to provide liquidity and hedging around all forms of futures markets. We could have a prediction market for “will the price of bitcoin be more than ten thousand dollars on the first of January 2019.”
All futures markets could be migrated to the blockchain using prediction markets. Likewise, all betting, such as online sports betting, could be more securely and efficiently run on blockchain platforms.
Migrating all of these disparate betting, derivatives and futures markets, to the blockchain could create a much more interoperable system where different networks could automatically draw upon the wisdom of a given network through APIs that connect into the price of the token.
These prediction markets could work as networks that aggregate the best knowledge that we have about a given unknown event. With the knowledge in those networks then being accessible for automatic external use in smart contracts via APIs.
A smart contract ensuring a wedding event could plug into a token market predicting the outcome for the weather on a certain day and use the token price to calculate the likelihood and cost of a weather disturbance to formulate the cost of the insurance claim.