Blockchain-Based Prediction Markets: A Survey of Architectures and Economic Mechanisms
DOI:
https://doi.org/10.59247/ijase.v3i1.161Keywords:
Automated Market Maker, Blockchain, Decentralized Finance, Prediction Markets, OracleAbstract
Prediction markets harness dispersed knowledge to forecast uncertain events. Blockchain technology has enabled a new generation of permissionless, oracle-dependent prediction platforms with diverse architectural and economic designs. To survey the engineering architectures, market microstructure, oracle designs, and economic mechanisms of operational blockchain-based prediction market platforms, using a structured comparative case-study approach. A documented platform-selection protocol (informed by Chong et al. [2019] and Treiblmaier [2019] for blockchain case-study research) was applied across DeFi literature, industry documentation, and technical whitepapers. Six blockchain-native platforms and one centralized regulated benchmark were selected based on market relevance, architectural diversity, and documentation availability. The six blockchain-native platforms—Polymarket, Augur, Gnosis Conditional Tokens/Omen, Azuro, SX Bet, and Overtime Markets—span three dominant architectural paradigms: the centralized limit order book with decentralized settlement, the fully on-chain automated market maker, and the modular conditional token infrastructure. Oracle design emerges as the critical security bottleneck across all platforms, with each adopting distinct trust assumptions and economic security models. Liquidity models range from hierarchical pooled AMMs to competitive order books to parimutuel systems, with no single architecture dominant across applications. Conclusions: The contrast between blockchain-native platforms and the CFTC-regulated Kalshi illustrates the fundamental trade-off between cryptographic trust minimization and regulatory compliance. These findings provide a structured framework for understanding the design space of blockchain-based prediction markets and identify open challenges including oracle security, cross-chain liquidity aggregation, and the integration of prediction market signals with autonomous decision-making systems.
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