People can gamble on almost anything; elections, sports, the Olympics. But bets in the immediate future will be made on the blockchain, with terms and markets defined by users.
Gnosis, a new Ethereum-powered platform, aims to bring prediction markets to the masses and allow anyone to create a market. Matthew Liston, Strategist at Gnosis, recently delivered a presentation outlining the platform, its aims, and applications.
Described as a ‘decentralized, prediction market’, Gnosis is based on the Ethereum blockchain. A prediction market allows anyone, anywhere to buy and sell shares in an outcome of any event. Such a decentralized platform should encourage those with unique and valid information or insights to come forward to the market and ‘price in’ their information.
Gnosis is not the custodian of any funds, all of which are held in smart contracts. This comes with the advantage that no counterparty risk is borne by users, so they do not have to trust Gnosis. But more importantly, the Ethereum blockchain will allow Gnosis to become a permissionless platform for all.
Furthermore, it is what you can derive from prediction markets, as Liston explained, that will generate interest in Gnosis,
“Prediction markets are an interesting because of what you can build on top of them…”
The Information Economy…
For instance, a prediction market can be built on an instrument on specific metrics. For example, what will China’s Gross Domestic Product (GDP) growth rate be in Q4 2016? A prediction market can be created, allowing research firms to sell their research directly and lead to more efficient markets.
Moreover, Gnosis will allow the replication of existing instruments but with lower fees. For example, binary options are a popular financial instrument. These take the form of either a call or put option, where a call option is used when you think the price of an asset will be higher after a certain period of time and vice versa. At the expiry date, you either receive a payout or lose.
But also, Gnosis will allow information aggregation to provide predicted probabilities of events which could make markets more efficient; by allowing agents to brace for and understand the likelihood of the outcomes of impactful events such as Brexit, the US presidential election and so on.
If we can aggregate information and find predicted probabilities, we can then act accordingly and use this information to prepare.
Liston also gave an interesting insight into how Gnosis could be used to provide action incentives. For example, suppose Apple wants to know whether there are any security breaches in their software package, say Safari for example. Apple could then create the following prediction market; ‘is there a zero day exploit in Safari?’.
Then Apple could spend $100,000 in the ‘No’ position. In creating this prediction market, in effect, it incentivizes security experts to find flaws in their software and locate any zero-day exploits in Safari. By putting a wager for $100, the security expert would obtain a large payoff for betting ‘Yes’ in this market along with presenting an exploit that was previously unseen or overlooked.
Therefore, Gnosis also has the potential to incentivize experts to help companies through prediction markets, facilitating transfers of knowledge.
Welcome to the Future…
‘Futarchy’; a governance solution for national, organisational and local structures, is an intriguing concept that drives Gnosis. In essence, we would bet on beliefs but vote on values. Futarchy entails voting for elected representatives to define a set of national goals and then betting on the ways to achieve these goals.
For example, Liston provides the example of funding an infrastructure project. Two prediction markets are then created. For one, the market will try to predict what the GDP of the country will be if the project is implemented. Whereas for the other market, it asks what will the GDP be if the project is not implemented.
Only those individuals who have valuable information or insights for the problem at hand will potentially make money from betting on the outcome. Moreover, research firms as mentioned earlier, could directly sell their research and inform participants as to what outcome is more likely.
At the end of the given time period, one market will have a higher estimate of GDP than the other. The policy decision will then be based on the market with the higher estimate and hence the more ‘desirable’ outcome. Then after the actual GDP figures are made available, this is plugged into the platform and those that predicted correctly would win money.
Risk and Reward…
Although the concept sounds very useful, it comes with some risks. Firstly, the right indicator and right time period will both be difficult to determine to optimize the functioning of prediction markets. For example, is GDP the ideal measure to use and should we aim to increase GDP? Moreover, GDP is also affected by various factors and could interfere with the incentives provided by the policy-decision making process.
Secondly, Futarchy is also prone to market manipulation. Liston gives the examples of a prediction market created to find out the change in the company’s share price if they replace the CEO.
In this instance, the CEO could get into the market, manipulating the predicted share price if he leaves the company. By taking large positions on the side of the market that thinks the share price will fall, the process of Futarchy would suggest to keep the CEO, when in fact, the CEO has made it look as if the share price will fall if he departs.
It is also unclear how the platform will prevent collusion between a small prediction market with only a few players. Nevertheless, Hanson et al. have researched the problem of market manipulation in prediction markets. While economics does not have laboratory-style experiments, the closest the discipline comes to hard science is through the use of experimental markets; typically volunteers are asked to participate and obtain real payouts, dependent on their strategies.
The results of the experiment suggest that when agents suspect there are manipulators present, and know which direction they are pushing the market, non-manipulators are reluctant to accept higher (or lower) offers, cancelling out the distortionary effect.
However, to research potential problems such as market manipulation further and find a way to outgrow these problems, the Ethereum Foundation has provided a developer grant to Gnosis. Liston explains that Gnosis is,
“focussed on being a prediction market platform… Anyone can create markets… anyone can offer Oracle services”.
Gnosis Crowdsale Set for September
The crowdsale for Gnosis will begin a week before DevCon2 and proceeds are earmarked for funding the Gnosis DAO, which is tasked with building, running and governing the Gnosis platform. Moreover, some proceeds will also go toward the Gnosis fund, which will invest in projects built on top of the Gnosis platform.
Similar to the Hollywood Stock Exchange, Gnosis aims to become a more generalized platform that consistently and correctly predicts outcomes, through participation in the buying and selling of shares. Hopefully, it will produce results such as increasing the efficiency of markets. On top of that, a range of applications and the development of a ‘Futarchy’ will be worth keeping a close eye on.