英文标题：
《Empirical properties of inter-cancellation durations in the Chinese
  stock market》
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作者：
Gao-Feng Gu, Xiong Xiong, Wei Zhang, Yong-Jie Zhang and Wei-Xing Zhou
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最新提交年份：
2014
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英文摘要：
  Order cancellation process plays a crucial role in the dynamics of price formation in order-driven stock markets and is important in the construction and validation of computational finance models. Based on the order flow data of 18 liquid stocks traded on the Shenzhen Stock Exchange in 2003, we investigate the empirical statistical properties of inter-cancellation durations in units of events defined as the waiting times between two consecutive cancellations. The inter-cancellation durations for both buy and sell orders of all the stocks favor a $q$-exponential distribution when the maximum likelihood estimation method is adopted; In contrast, both cancelled buy orders of 6 stocks and cancelled sell orders of 3 stocks prefer Weibull distribution when the nonlinear least-square estimation is used. Applying detrended fluctuation analysis (DFA), centered detrending moving average (CDMA) and multifractal detrended fluctuation analysis (MF-DFA) methods, we unveil that the inter-cancellation duration time series process long memory and multifractal nature for both buy and sell cancellations of all the stocks. Our findings show that order cancellation processes exhibit long-range correlated bursty behaviors and are thus not Poissonian.
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中文摘要：
订单取消过程在订单驱动股票市场的价格形成动力学中起着至关重要的作用，在计算金融模型的构建和验证中起着重要作用。基于2003年深圳证券交易所18只流通股的订单流数据，我们以两次连续取消之间的等待时间为单位，研究了取消间隔时间的经验统计特性。当采用最大似然估计方法时，所有股票的买入和卖出指令的相互抵消持续时间均呈指数分布；相比之下，当使用非线性最小二乘估计时，6只股票的取消买入指令和3只股票的取消卖出指令都倾向于威布尔分布。应用去趋势波动分析（DFA）、中心去趋势移动平均（CDMA）和多重分形去趋势波动分析（MF-DFA）方法，我们揭示了对所有股票的买入和卖出取消，取消时间序列都具有长记忆性和多重分形性质。我们的研究结果表明，订单取消过程表现出长程相关的突发行为，因此不是泊松过程。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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