Evidence map›Paper›PMID 35463295›Full record

ArticleFinance research letters2022

Information disclosure of COVID-19 specific medicine and stock price crash risk in China.

Jiangjiao Duan, Jingjing Lin

Abstract read
In one paragraph

Article in Finance research letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jiangjiao DuanBusiness School, University of Shanghai for Science and Technology, Shanghai, China.
Jingjing LinBusiness School, University of Shanghai for Science and Technology, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the impact of information disclosure of COVID-19 specific medicine on stock price crash risk. To achieve this goal, crawling massive announcements of listed companies in China and using OCR (optical character recognition) to abstract text, texture analysis is adopted to count the keywords occurrence, which derives from a keywords list consisted of "specific medicine", "vaccine" and others. Based on information disclosure of COVID-19 specific medicine, empirical tests are conducted. The results show that the abnormal COVID-19 disclosure intensifies the degree of stock price crash risk. It proves that information asymmetry exactly exists in listed company information disclosure process in the securities market. It also provides new evidence that exaggerated information disclosure caused stock prices crash.

Indexed as

COVID-19Information disclosureStock price crash risk

Identifiers

PMID35463295
PMCPMC9013702

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.