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Empirical properties of inter-cancellation durations in the Chinese stock market

机译:中国股票市场取消期间的经验特性

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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 23 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 9 stocks and cancelled sell orders of 4 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.
机译:在订单驱动的股票市场中,订单取消过程在价格形成的动态中起着至关重要的作用,并且在计算金融模型的构建和验证中也很重要。基于2003年在深圳证券交易所交易的23种流动性股票的订单流数据,我们研究了以事件为单位的取消间持续时间的经验统计特性,该事件被定义为两次连续取消之间的等待时间。当采用最大似然估计方法时,所有股票的买卖订单的取消时间之间的持续时间有利于$ q $指数分布;相反,当使用非线性最小二乘估计时,两个9个股票的取消买入订单和4个股票的取消卖出订单都更倾向于Weibull分布。应用去趋势波动分析(DFA),居中去趋势移动平均(CDMA)和多分形去趋势波动分析(MF-DFA)方法,我们揭示出取消持续时间序列处理长记忆和多分形性质,从而消除了交易的取消所有的股票。我们的发现表明,订单取消过程显示出长期相关的突发行为,因此不是泊松现象。

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