组合预测市场中基于交易的动态连接树资产模型
Trade-based Asset Model using Dynamic Junction Tree for Combinatorial Prediction Markets
摘要：
预测市场已经证明了它们在汇集集体专业知识方面的价值。组合预测市场不仅允许对基本事件进行预测，还允许对事件的条件和/或布尔组合进行预测。我们描述了一个基于交易的组合预测市场资产管理系统，称为动态资产集群（DAC），提高了时间和空间效率的方法，它保持并行连接树的资产和概率。基本数据结构是资产块，它简洁地表示用户进行的一组交易。用户的资产模型由一组代表用户整个交易历史的资产块组成。从资产块动态创建连接树，以计算用户的最小和预期资产。
英文摘要：
Prediction markets have demonstrated their value for aggregating collective expertise. Combinatorial prediction markets allow forecasts not only on base events, but also on conditional and/or Boolean combinations of events. We describe a trade-based combinatorial prediction market asset management system, called Dynamic Asset Cluster (DAC), that improves both time and space efficiency over the method of, which maintains parallel junction trees for assets and probabilities. The basic data structure is the asset block, which compactly represents a set of trades made by a user. A user's asset model consists of a set of asset blocks representing the user's entire trade history. A junction tree is created dynamically from the asset blocks to compute a user's minimum and expected assets.
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