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Augur: The Theory behind the First Decentralized Prediction Markets Platform

Jul 11, 2018, 1:47PM
10 min, 14 sec READ

An absolutely comprehensive look at Augur just days after the launch of its mainnet. Everything you wanted to know, right here.

Put simply, Augur allows users to forecast the outcome of events and receive monetary rewards if correct; the less likely the event, the greater the reward on a correct prediction. The U.S.-based company, one of the very first crowdfundings to launch on Ethereum, was founded in 2014 by Jack Peterson and Joey Krug. The platform functions as a kind of oracle, driven by economic incentivization to unambiguously frame valid questions/markets and accurately report answers to resolve markets. Prediction markets are essentially markets for buying and selling predictions - also known as event derivatives and idea futures. Among the different use cases of Augur are political forecasting, event hedging, company forecasting, and weather prediction. 

Among project advisors, one notably finds Intrade founder Ron Bernstein and economics professor Robin Hanson, known for having coined the notion of futarchy - a system of government where elected officials prescribe measures of welfare while prediction markets determine the most effective policies.

Although Augur is a decentralized platform running on Ethereum's programmable blockchain, The Forecast Foundation was set up by the Augur founders as the entity committed to ensuring the continued support and development of the Augur platform, using bounties as an incentive - the first high severity bounty having been paid just prior to mainnet launch.

As the first decentralized prediction market, Augur is intended as a public service, freely accessible. Just one day after launch, there is already significant volume (active markets can be tracked here without running an Augur node).

Augur's Legacy

The platform, one of the most eagerly anticipated projects in the crypto space, is in a way a successor to the legendary Intrade, an Ireland-based prediction markets platform that ceased operations in March 2013 as a result of "financial irregularities" to do with cross-jurisdictional regulatory issues. In the same footsteps, Augur aims to generalize derivatives in a single forecasting meta-tool and is initially geared towards people with experience in trading on existing traditional markets such as stocks, commodities, futures, options, and so on.

As a significant historical experiment, Augur is inspired by a number of concepts and ideas that preceded it; it is essentially a decentralized actor-network, which satisfies the conditions necessary for coherently bringing these ideas together in a functional whole. This is also why Augur's key differentiator is that it puts particular emphasis on strong decentralization as a crucial property of the system and one that ensures its resilience to censorship or capture.

Decentralization is furthermore important for an efficient prediction market as centralized prediction markets are hindered by a number of liabilities and drawbacks (e.g., do not allow global participation, limit the types of markets that can be created and require traders to trust the market operators) and tend to eventually get shut down by governments. Running markets on a decentralized blockchain eliminate the single points of failure that centralized prediction markets are liable to.

The Efficient Market Hypothesis

Prediction markets as a tool test one of the most important questions in economics - how markets absorb information. The Efficient Market Hypothesis (EMH) is a theory according to which it is impossible to consistently beat the market since assets are already accurately priced, reflecting all available information about them. The EMH comes in three forms, each implying that information at different levels is impounded in an asset’s price:

  • Strong: Assumes that all public and private (hidden or insider) information is impounded.
  • Semi-Strong: Assumes that all public (historical, news, annual reports, etc.) is impounded in the price, and price is rapidly changing to accommodate new public information as it becomes available.
  • Weak: All historic and publicly available information is reflected in the price.

It is assumed that when taken to decentralized prediction markets, all relevant information is extracted in the price with the possibility of manipulation almost eliminated (“insider trading” is encouraged).

The Wisdom of Crowds

In his popular 2004 book "The Wisdom of Crowds" financial journalist James Surowiecki investigates the accuracy of collective predictions against those of expert opinions, citing experiments and conducted research. The University of North Carolina, Oxford University, and others have conducted studies indicating how prediction markets provide superior forecasting for event outcomes to traditional forecasting methods.

Surowiecki provides examples and observations of how the combined guesstimates of diverse opinions that blend together a plethora of independent views tend to eliminate group-think bias and produce much more accurate predictions that routinely outperform expert opinions and individual specialists alone.

Surowiecki, however, highlights three measures that separate ‘wise’ crowds plain ‘group-think psychology’:

  • diversity of information,
  • independence of decision,
  • organizational decentralization.

Each wager is an opinion adding each individual’s knowledge to the crowd’s predictive muscle. Augur harnesses this uncanny ability of groups to make smart decisions at scale to build a powerful forecasting meta-tool for aggregating crowdsourced insights and rating trust proxies using the crowd.

Friedrich Hayek and The Use of Knowledge in Society

“The Use of Knowledge in Society" is an influential scholarly essay written by Austrian economist Friedrich Hayek in 1945 that best captures the concept of prediction markets and their economic benefits. Hayek’s article argues against the institution of a centrally planned economy governing prices, highlighting the dynamism and organic nature of market price fluctuations and the benefits of that reality.

He argues that a centrally planned economy could never equal the efficiency of the open market because a single agency or agent is only a fraction of the sum total of knowledge held by all members of society. And as knowledge is unevenly distributed among members of society, a decentralized economy of decisions made by those with local knowledge is best suited to instrumentalize markets efficiently. Consequently, by virtue of having better prediction markets, one has better information available to make decisions, necessitating that planning and control over resources should be decentralized.

The idea is best captured in the following extracts from the essay.

The peculiar character of the problem of a rational economic order is determined precisely by the fact that the knowledge of the circumstances of which we must make use never exists in concentrated or integrated form but solely as the dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess. The economic problem of society is thus not merely a problem of how to allocate “given” resources—if “given” is taken to mean given to a single mind which deliberately solves the problem set by these “data.” It is rather a problem of how to secure the best use of resources known to any of the members of society, for ends whose relative importance only these individuals know. Or, to put it briefly, it is a problem of the utilization of knowledge which is not given to anyone in its totality (I). 

Far from being concentrated, then, knowledge is distributed across a broad range of systems, disciplines and individuals. Moreover, the decentralization of knowledge furthers agility and the speedy transference of knowledge,  

If we can agree that the economic problem of society is mainly one of rapid adaptation to changes in the particular circumstances of time and place, it would seem to follow that the ultimate decisions must be left to the people who are familiar with these circumstances, who know directly of the relevant changes and of the resources immediately available to meet them. We cannot expect that this problem will be solved by first communicating all this knowledge to a central board which, after integrating all knowledge, issues its orders. We must solve it by some form of decentralization. But this answers only part of our problem. We need decentralization because only thus can we insure that the knowledge of the particular circumstances of time and place will be promptly used. But the “man on the spot” cannot decide solely on the basis of his limited but intimate knowledge of the facts of his immediate surroundings. There still remains the problem of communicating to him such further information as he needs to fit his decisions into the whole pattern of changes of the larger economic system.

Distributed knowledge eventually funnels down until it overlaps and converges into a unified, whole picture,

The whole acts as one market, not because any of its members survey the whole field, but because their limited individual fields of vision sufficiently overlap so that through many intermediaries the relevant information is communicated to all. The mere fact that there is one price for any commodity—or rather that local prices are connected in a manner determined by the cost of transport, etc.—brings about the solution which (it is just conceptually possible) might have been arrived at by one single mind possessing all the information which is in fact dispersed among all the people involved in the process (V). 

We must look at the price system as such a mechanism for communicating information if we want to understand its real function—a function which, of course, it fulfills less perfectly as prices grow more rigid. The most significant fact about this system is the economy of knowledge with which it operates, or how little the individual participants need to know in order to be able to take the right action. In abbreviated form, by a kind of symbol, only the most essential information is passed on and passed on only to those concerned (VI).

Hayek is known for formulating the function of market prices in succinctly communicating information as economic signals that trigger the behaviors driving the economic calculus. Augur follows in the Hayekian reasoning given that in a prediction market thousands of participating actors could report on the outcome of a single event, extracting valuable information which market mechanisms reflect and price in, consequently making for more efficient economic coordination and resource allocation.

Complete Markets

Kenneth Arrow and Gerard Debreu ended up winning a Nobel Prize for their theory of “complete markets”. In economics, a complete market concerns utility maximization and a market is said to be complete if it satisfies two conditions, namely,

  • Negligible transaction costs, giving rise to perfect information.
  • Assets are state-contingent and there is a price for every asset in every possible state of the world (e.g., an umbrella when it rains is different from an umbrella when it doesn’t).

A complete market is one where contingent claims for all possible states of the world are available and a complete system of markets is one in which there is a market for every good (one is able to speculate on anything) - a "good" in this case, includes the date and environment in which a commodity is consumed, containing the consumption, production and investment choices in an uncertain, multi-period world. As a prediction market, Augur aims to develop into a dynamically complete market for hedging against world events and previously undiversifiable risks.


Intrade, a now-defunct site that was for some time known as "the world's leading prediction market", is in some ways the direct precursor of Augur (many of the people that had previously worked at Intrade are now working on Augur). Intrade's system was designed to evoke sophisticated investment that rewarded analytical calculation over partisanship and wishful thinking, attracting an avid community of traders, particularly in the domain of politics in measuring political futures through real prices.

However, within months of the 2012 election the company had collapsed under the weight of a U.S. government lawsuit. The 2010 Dodd-Frank financial reform specifically bans futures related to terrorism, assassination, gaming, or anything "contrary to the public interest," and in 2012 it was suggested that this goes to also cover elections.

More to Come

So far, we've looked at Augur's theoretical, philosophical and historical roots. In the second and final part of this series we will look at Augur's technological infrastructure; from the platform workings to the REP token to its use cases, we will lay down everything there is to know about this exciting platform. Follow us and be the first to know about the upcoming article.    

Disclaimer: information contained herein is provided without considering your personal circumstances, therefore should not be construed as financial advice, investment recommendation or an offer of, or solicitation for, any transactions in cryptocurrencies.