论文标题
私人呼叫拍卖和市场影响
Differentially Private Call Auctions and Market Impact
论文作者
论文摘要
我们提出和分析私人（DP）呼叫拍卖机制，以替代现代电子市场中常见的复杂和临时隐私工作。我们证明，DP机制中清除的股票数量与非私有化的最佳相比，并提供了匹配的下限。我们分析了市场参与者自然无重组学习动态下我们机制的激励性能及其行为。我们包括模拟结果以及与市场影响的金融文献的联系。
We propose and analyze differentially private (DP) mechanisms for call auctions as an alternative to the complex and ad-hoc privacy efforts that are common in modern electronic markets. We prove that the number of shares cleared in the DP mechanisms compares favorably to the non-private optimal and provide a matching lower bound. We analyze the incentive properties of our mechanisms and their behavior under natural no-regret learning dynamics by market participants. We include simulation results and connections to the finance literature on market impact.
