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Complexity Changes in the US and China's Stock Markets: Differences, Causes, and Wider Social Implications

文献类型：期刊论文

作者Gao, Jianbo1,2,3; Hou, Yunfei4; Fan, Fangli1; Liu, Feiyan3,5
刊名ENTROPY
出版日期2020
卷号22期号:1页码:13
关键词EMH Lempel-Ziv complexity permutation entropy Hurst parameter the US and China's stock market
DOI10.3390/e22010075
通讯作者Hou, Yunfei(yunfei.mz@gmail.com) ; Liu, Feiyan(liufeiyan1984@gmail.com)
英文摘要How different are the emerging and the well-developed stock markets in terms of efficiency? To gain insights into this question, we compared an important emerging market, the Chinese stock market, and the largest and the most developed market, the US stock market. Specifically, we computed the Lempel-Ziv complexity (LZ) and the permutation entropy (PE) from two composite stock indices, the Shanghai stock exchange composite index (SSE) and the Dow Jones industrial average (DJIA), for both low-frequency (daily) and high-frequency (minute-to-minute)stock index data. We found that the US market is basically fully random and consistent with efficient market hypothesis (EMH), irrespective of whether low- or high-frequency stock index data are used. The Chinese market is also largely consistent with the EMH when low-frequency data are used. However, a completely different picture emerges when the high-frequency stock index data are used, irrespective of whether the LZ or PE is computed. In particular, the PE decreases substantially in two significant time windows, each encompassing a rapid market rise and then a few gigantic stock crashes. To gain further insights into the causes of the difference in the complexity changes in the two markets, we computed the Hurst parameter H from the high-frequency stock index data of the two markets and examined their temporal variations. We found that in stark contrast with the US market, whose H is always close to 1/2, which indicates fully random behavior, for the Chinese market, H deviates from 1/2 significantly for time scales up to about 10 min within a day, and varies systemically similar to the PE for time scales from about 10 min to a day. This opens the door for large-scale collective behavior to occur in the Chinese market, including herding behavior and large-scale manipulation as a result of inside information.
WOS关键词LONG-RANGE DEPENDENCE ; LEMPEL-ZIV COMPLEXITY ; HURST EXPONENT ; PERMUTATION ENTROPY ; EMERGING MARKETS ; EFFICIENCY ; PREDICTION ; TIME ; PATTERNS ; PRICES
资助项目National Natural Science Foundation of China[71661002] ; National Natural Science Foundation of China[41671532] ; China Postdoctoral Science Foundation[2016M592605] ; Fundamental Research Funds for the Central Universities in China ; National Science Foundation
WOS研究方向Physics
语种英语
WOS记录号WOS:000516825400014
出版者MDPI
资助机构National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Fundamental Research Funds for the Central Universities in China ; National Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/38761]  
专题数字内容技术与服务研究中心_听觉模型与认知计算
通讯作者Hou, Yunfei; Liu, Feiyan
作者单位1.Beijing Normal Univ, Fac Geog Sci, Ctr Geodata & Anal, Beijing 100875, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Guangxi Univ, Int Coll, Nanning 530004, Peoples R China
4.Wuhan Univ, Sch Econ & Management, Wuhan 430072, Peoples R China
5.CityDO, Hangzhou 310000, Peoples R China
推荐引用方式
GB/T 7714		 Gao, Jianbo,Hou, Yunfei,Fan, Fangli,et al. Complexity Changes in the US and China's Stock Markets: Differences, Causes, and Wider Social Implications[J]. ENTROPY,2020,22(1):13.
APA Gao, Jianbo,Hou, Yunfei,Fan, Fangli,&Liu, Feiyan.(2020).Complexity Changes in the US and China's Stock Markets: Differences, Causes, and Wider Social Implications.ENTROPY,22(1),13.
MLA Gao, Jianbo,et al."Complexity Changes in the US and China's Stock Markets: Differences, Causes, and Wider Social Implications".ENTROPY 22.1(2020):13.

入库方式： OAI收割

来源：自动化研究所

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