Price Interpretability of Prediction Markets: A Convergence Analysis
研究提出一种多变量效用机制，分析风险规避且信念多样的交易者与做市商反复互动时市场价格的收敛性，并给出近似算法，帮助市场设计者优化机制以更高效地汇集意见。
Prediction markets are renowned for their accuracy in forecasting. However, it is not fully clear how the predication market aggregates the traders’ beliefs. In “Price Interpretability of Prediction Markets: A Convergence Analysis,” Gao, Wang, Wu, and Yu introduce a novel multivariate utility (MU)-based mechanism that consolidates various existing automated market-making schemes. This mechanism establishes convergence results for markets consisting of risk-averse traders with diverse beliefs who interact repeatedly with the market maker. Furthermore, the study delivers analytical and numerical insights into the limiting price across different market models. Building on these results, the authors offer an efficient approximation scheme for the limiting price, shedding light on how traders’ beliefs shape market prices. These discoveries provide valuable guidance to market designers, enabling them to refine and optimize market-making mechanisms for more efficient opinion elicitation.