A preliminary research of prediction markets based on blockchain powered smart contracts
文献类型：会议论文
| 作者 | Shuai Wang ; Xiaochun Ni; Yong Yuan; Xiao Wang; Liwei Ouyang; Fei-Yue Wang
|
| 出版日期 | 2018 |
| 会议日期 | 30 Jul.- 3 Aug., 2018. |
| 会议地点 | Halifax, Canada |
| 英文摘要 | ; Prediction markets are markets where participants trade contracts whose payoffs are tied to a future event, there by yielding prices that can be interpreted as market aggregated forecasts. Past studies have shown that the prediction markets can provide accurate forecasts, sometimes better than sophisticated statistical tools. Due to their advantages, prediction markets have been widely used in the prediction of elections, project management, product quality, and impact of events. However, prediction markets also have some limitations, e.g., poor anonymity and limited market liquidity. In this paper, we propose to apply blockchain powered smart contracts to the prediction markets. First, we give a comprehensive overview on the prediction markets, including their theoretical basis, classification and applications. Second, we present how to design prediction markets based on smart contracts. Then, the algorithm of contracts implementation is proposed. Finally, in order to verify the effectiveness of the algorithm, an intraenterprise prediction market is built based on a private blockchain. The experimental results show that the market can make accurate prediction for a particular event. In addition, the autonomy, self-sufficiency, and decentralization characteristics of blockchain make the prediction markets more efficient and robust. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21814]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 作者单位 | Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100864, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shuai Wang,Xiaochun Ni,Yong Yuan,et al. A preliminary research of prediction markets based on blockchain powered smart contracts[C]. 见:. Halifax, Canada. 30 Jul.- 3 Aug., 2018.. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。