Evidence map›Paper›PMID 36673177›Full record

ArticleEntropy (Basel, Switzerland)2022

Precision Measurement of the Return Distribution Property of the Chinese Stock Market Index.

Peng Liu, Yanyan Zheng

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Peng LiuSchool of Information, Xi'an University of Finance and Economics, Xi'an 710100, China.ORCID 0000-0002-9115-2055
Yanyan ZhengSchool of Management, Xi'an Polytechnic University, Xi'an 710048, China.ORCID 0000-0002-1092-072X

Funding

Education Department of Shaanxi Provincial Government, P.R. China 19JK0355Humanities and Social Sciences Youth Foundation of the Chinese Ministry of Education 22YJCZH107Scientific Research Support Program of Xi'an University of Finance and Economics 22FCZD03
6 · The paper itself

Abstract

In econophysics, the analysis of the return distribution of a financial asset using statistical physics methods is a long-standing and important issue. This paper systematically conducts an analysis of composite index 1 min datasets over a 17-year period (2005−2021) for both the Shanghai and Shenzhen stock exchanges. To reveal the differences between Chinese and mature stock markets, we precisely measure the property of the return distribution of the composite index over the time scale Δt, which ranges from 1 min to almost 4000 min. The main findings are as follows: (1) The return distribution presents a leptokurtic, fat-tailed, and almost symmetrical shape that is similar to that of mature markets. (2) The central part of the return distribution is described by the symmetrical Lévy α-stable process, with a stability parameter comparable with a value of about 1.4, which was extracted for the U.S. stock market. (3) The return distribution can be described well by Student’s t-distribution within a wider return range than the Lévy α-stable distribution. (4) Distinctively, the stability parameter shows a potential change when Δt increases, and thus a crossover region at 15 <Δt< 60 min is observed. This is different from the finding in the U.S. stock market that a single value of about 1.4 holds over 1 ≤Δt≤ 1000 min. (5) The tail distribution of returns at small Δt decays as an asymptotic power law with an exponent of about 3, which is a widely observed value in mature markets. However, it decays exponentially when Δt≥ 240 min, which is not observed in mature markets. (6) Return distributions gradually converge to a normal distribution as Δt increases. This observation is different from the finding of a critical Δt= 4 days in the U.S. stock market.

Indexed as

Chinese stock market indexeconophysicspower-lawreturn distributionsociophysics

Identifiers

PMID36673177
PMCPMC9857575

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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.