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中国股票市场中大单与小单交易指令的复杂性行为

The Complexity Behavior of Big and Small Trading Orders in the Chinese Stock Market.

作者信息

Zhu Yu, Fang Wen

机构信息

Department of Finance, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.

出版信息

Entropy (Basel). 2023 Jan 4;25(1):102. doi: 10.3390/e25010102.

DOI:10.3390/e25010102
PMID:36673243
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9858074/
Abstract

The Chinese stock market exhibits many characteristics that deviate from the efficient market hypothesis and the trading volume contains a great deal of complexity information that the price cannot reflect. Do small or big orders drive trading volume? We studied the complex behavior of different orders from a microstructure perspective. We used ETF data of the CSI300, SSE50, and CSI500 indices and divided transactions into big and small orders. A multifractal detrended fluctuation analysis (MFDFA) method was used to study persistence. It was found that the persistence of small orders was stronger than that of big orders, which was caused by correlation with time. A multiscale composite complexity synchronization (MCCS) method was used to study the synchronization of orders and total volume. It was found that small orders drove selling-out transactions in the CSI300 market and that big orders drove selling-out transactions in the CSI500 market. Our findings are useful for understanding the microstructure of the trading volume in the Chinese market.

摘要

中国股票市场呈现出许多偏离有效市场假说的特征，且交易量包含大量价格无法反映的复杂信息。是小订单还是大订单推动了交易量？我们从微观结构角度研究了不同订单的复杂行为。我们使用了沪深300、上证50和中证500指数的交易型开放式指数基金（ETF）数据，并将交易分为大订单和小订单。采用多重分形去趋势波动分析（MFDFA）方法研究持续性。结果发现，小订单的持续性强于大订单，这是由与时间的相关性导致的。采用多尺度复合复杂性同步（MCCS）方法研究订单与总量的同步性。结果发现，小订单推动了沪深300市场的抛售交易，而大订单推动了中证500市场的抛售交易。我们的研究结果有助于理解中国市场交易量的微观结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77a1/9858074/1bb2a39d947b/entropy-25-00102-g011.jpg
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