发表机构
University of Illinois; Purdue University（伊利诺伊大学; 普渡大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出价差门控霍克斯-群聚模型刻画最优买卖价动态，在真实数据上验证其优势，并推导限价单最优规模的闭式解。
AI 中文摘要
我们研究了一种价差门控霍克斯-群聚模型下最优买价和卖价的联合动态。该模型追踪四种类型的最优报价变动：当价差处于一个最小跳动时，价差收窄变动被关闭；一个跨侧激发项，其激活取决于当前价差，将订单簿两侧联系起来。我们证明了该过程在任何有限时间范围内都是非爆炸的，给出了一个O(N)递归似然，并通过模拟验证了最大似然估计器。在两只大跳动股票INTC和MSFT的日内限价订单簿真实数据上，去除跨侧项的限制被拒绝，完整模型通过AIC和BIC显著改善了拟合；由于单日似然是多模态的，估计采用多起点搜索。作为一个应用，我们根据模型的下一事件概率和外部提供的执行概率，推导了在最优或次优报价处放置的单期限价单的最优规模的闭式解。
英文摘要
We study the joint dynamics of the best bid and ask prices with a spread-gated Hawkes-flocking model. The model tracks four types of best-quote movements: spread-narrowing movements are switched off when the spread is at its one-tick minimum, and a cross-side excitation term, whose activation depends on the prevailing spread, links the two sides of the book. We show that the process is non-explosive on every finite horizon, give an $O(N)$ recursive likelihood, and validate the maximum likelihood estimator by simulation. On real intraday limit order book data for two large-tick stocks, INTC and MSFT, the restriction that removes the cross-side term is rejected, and the full model improves fit substantially by AIC and BIC; the likelihood is multimodal on a single day, so estimation uses a multi-start search. As an application, we derive the closed-form optimal size of a single-period limit order placed at the best or second-best quote, given the model's next-event probabilities and externally supplied execution probabilities.
