Evidence map›Paper›PMID 36673243›Full record

ArticleEntropy (Basel, Switzerland)2023

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

Yu Zhu, Wen Fang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yu ZhuDepartment of Finance, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.
Wen FangDepartment of Finance, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.

Funding

National Natural Science Foundation of China 72101020
6 · The paper itself

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.

Indexed as

Chinese marketcomplexity behaviormicrostructuretrading ordervolume

Identifiers

PMID36673243
PMCPMC9858074

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.