A permissioned blockchain-based implementation of LMSR prediction markets.

Since the seminal work by Hanson (2003), the Logarithmic Market Scoring Rule (LMSR) has become the de facto market-maker mechanism for prediction markets. We suggest in this paper three potential issues with centralized implementations of LMSR, which we refer to as the availability, security, and privacy problems. We also explain how a permissioned blockchain-based implementation of LMSR effectively solves all the above problems. Following the design science research framework (Peffers et al., 2007), our main contribution is a fully functional permissioned blockchain-based implementation of LMSR that is ready to be deployed. We believe our results are of great value not only to prediction market researchers and practitioners looking for LMSR implementations, but also to blockchain professionals looking for fully developed solutions as well as applications of suitable research frameworks to guide blockchain research and development.