EXAMENSARBETE INOM TEKNIK, GRUNDNIVÅ, 15 HP STOCKHOLM, SVERIGE 2018 Blockchain and prediction markets An analysis of three organizations implementing prediction markets using blockchain technology, and the future of blockchain prediction market EMIL FRÖBERG, GUSTAV INGRE, SIMON KNUDSEN KTH SKOLAN FÖR INDUSTRIELL TEKNIK OCH MANAGEMENT PREDICTION MARKETS USING BLOCKCHAIN TECHNOLOGY 1 Abstract— Since the rise of Bitcoin in 2008, many have speculated implemented prediction markets thus enable accurate about the scope of blockchain technology applications. Prediction mar- predictions about a wide range of events. kets, i.e. markets in which uncertain outcomes of future events are trade- Although there are few real-world prediction markets able, is such an application; blockchain technology may offer several that have been successfully brought to the wide public, technological attributes that may facilitate prediction market implement- the proven ability of prediction markets to predict the ations. This study describes and compares the platforms of three organ- probability of future outcomes makes them an area of in- izations that build blockchain prediction market platforms: Augur, Gnosis terest for many. The recent emergence of blockchain tech- and Stox. By this, we provide a pertinent overview of current blockchain nology popularity has shed light on blockchain applic- prediction market applications. Additionally, we conduct interviews with ations that some argue will dramatically reshape whole three Swedish blockchain experts - clarifying blockchain technology strengths and weaknesses in relation to prediction markets. We identify industries; prediction markets is one of these applica- five factors that are essential for prediction markets to aggregate and tions. One key strentgth of blockchain is its decentral- reflect information accurately: many actors participating, no actors being ized nature: by the use of smart contracts automatically, prevented from participating, a trustworthy setting function, freedom to transparently and securely enabling creation of contracts create new contracts, and transparency. We conclude that blockchain and transactions without the need for a central authority technology has attributes that facilitate future prediction market imple- controlling who sends what to whom. This removes the mentations in accordance with these requirements. However, blockchain need for trust in a central authority - improving security. scalability issues pose a key challenge. Thus, prediction markets implemented using blockchain technology might be a truly disruptive concept. Keywords—Blockchain, Smart Contracts, Prediction Markets. A Research questions I: Introduction This article qualitatively describes and compares tech- nical aspects of three organizations that make up the Blockchain technology is a technological innovation that frontline of blockchain prediction markets (in this article has taken the world by storm. The technology can be hereafter referred to as BPMs): Augur, Gnosis and Stox. described as an unceasingly growing list of records, se- These three organizations unconnectedly aspire to intro- cured by cryptography. One of the first implementations duce prediction markets to the public soon, and as of of the blockchain technology is Bitcoin. Bitcoin is a digital May 2018 have tokens4 issued with a combined value of currency that enables users to transfer currency pseud- roughly $ 587 million (USD) according to Coinmarketcap onymously1 without the need for a central authority 2 (2018). In addition to the comparison of Augur, Gnosis regulating the transactions. Bitcoin’s whitepaper , writ- and Stox, we interview three persons that are involved ten by Nakamoto (2008) has served as a technical base in the development of blockchain applications. We try to for other blockchain-based technologies. More recently, answer three questions: the Ethereum Foundation has developed a multipurpose blockchain platform upon which developers can develop 1) Which similarities and differences exist between Augur, their own applications (Wood, 2014) and execute smart- Gnosis and Stox? contracts. Smart contracts offer a way of digitizing and 2) Which requirements does a prediction market that accur- automating the execution of contracts and was sugges- ately aggregates and reflects as much relevant information ted by Szabo (1997) before the existence of blockchain as possible need to meet? technology. Blockchain technology has wide usage; many 3) How do the blockchain-specific and application-specific types of services in which digital transactions of some implementations of Augur, Gnosis and Stox respectively type are required may be implemented using it. relate to the requirements in 2)? Prediction markets is a concept that dates to the late 19th century (Rhode and Strumpf, 2004) but has yet to B Purpose gain the attention of the masses. It can be described as an exchange traded market in which users can wager Prediction markets have the potential to bring value on the outcome of future events. Examples include the to many parts of society. Implementations vary from outcome of elections, weather and the success of new pricing of complicated contracts such as insurances, bug 5 products. This structure has proven to be more powerful bounty programs and predictions of economic macro than experts in predicting the outcomes of many types of factors. In short, prediction markets provide an accurate events, much due to the assumptions of the efficient mar- information collection mechanism that applies to more ket hypothesis3 (Wolfers and Zitzewitz, 2004). Efficiently areas than other alternatives such as polls and expert advise. Using blockchain technology, the need for a 1. The addresses of the sender/receiver are not anonymous, although central authority regulating a prediction market system the addresses are not connected to any personal information. 2. A document highlighting features of a product, idea or technology 4. i.e. tradable units on a blockchain. This is further explained in in a factual and non-pitching manner. Section 4.1.3 3. The efficient market hypothesis states that market prices incorpor- 5. Bug bounty is a concept incentivizing individuals to find software ate and reflect all relevant information. bugs. PREDICTION MARKETS USING BLOCKCHAIN TECHNOLOGY 2 is removed. By this, security and the need for trust is In 1996, HP conducted a study to forecast the sales reduced. Additionally transaction costs may be reduced. of several different product families. The results, illus- By answering the research questions introduced in the trated in Appendix C, show that forecasts made by previous subsection, we provide an evaluation of BPMs prediction markets often were more accurate than official in regard to a model of a prediction market that accur- forecasts. Based on the results of this study, Ho and Chen ately aggregates and reflects as much relevant publicly (2007) present a scientific foundation for why prediction available information as possible - suggesting answers markets work. They present five principles: Incentive, to what attributes are needed to develop a BPM that Indicator, Improvement, Independence and Crowd. The reflects available information efficiently. Through this, first principle relates to increasing the incentive among we hope to provide guidance to BPM developers, aca- market actors to participate in the market to make use of demics researching decentralized prediction markets, as all information held by the actors. The second principle well researchers scrutinizing the potential of blockchain is intended to convey clear information to the market technology applications. participants about the current status of the market, i.e. a clear indication of the aggregate information should be available to market participants. Thirdly, the mar- II: Background ket should have a function to encourage learning and thereby improving the markets and making them smarter A Previous studies through a continuous process of learning. Furthermore, Wolfers and Zitzewitz (2004) describe prediction markets the authors believe that pooling information from in- as markets whose payoffs depend on unknown future dependent sources will yield more accurate predictions. events. Even though much has changed since this art- Lastly, a prediction markets work best when a large num- icle’s publication in 2004, the authors accurately describe ber of people - a crowd, participates. The study comes to several applications of prediction markets. Specifically, the conclusion that a well-functioning prediction market prediction markets have proven to be able to outper- must adhere to all five principles. The authors also point form predictions from polling and experts in American out that even if a prediction market does not adhere to elections (J. Berg, Forsythe, Nelson and Rietz, 2008), all principles, it still poses as a better alternative than Australian elections (Wolfers and Leigh, 2002), printer traditional polling methods in many cases. sales (Plott and Chen, 2002) and Oscar winners (Pennock, Lawrence, Giles and Nielsen, 2001). B Prediction markets using blockchain Swan (2015) describes Blockchain as a technology that will continuously grow to deployments that reach bey- technology ond currency applications such as Bitcoin. She defines The most common way to implement an application Blockchain 1.0 as a state in which blockchain applications using blockchain technology is to use the technology of are limited to applications related to cash –