CSNCD: China Stock News Co-mention Dataset

9 Pages Posted: 29 Nov 2023

See all articles by Shuyi Ge

Shuyi Ge

Nankai University - Department of Finance

Shaoran Li

Peking University

Xinping Li

Peking University - School of Economics

Xianglong Yan

Peking University - School of Economics

Hanyu Zheng

The University of Hong Kong - Faculty of Business and Economics

Date Written: November 11, 2023

Abstract

In this paper, we introduce the first dataset that records the news co-mention relationships in the Chinese A-share market. In total, we collected 1,138,247 pieces of news articles that at least mentioned one listed firm in the A market from major Chinese media and financial websites from September 1999 to December 2022. The development of this dataset could enable data scientists and financial economists to investigate the network of stocks through news co-mention in the Chinese stock market. The dataset could also help to construct novel portfolio strategies like the cross-firm momentum strategy with news-implied links as in Ge et al (2023).

Keywords: Big data; News; Chinese stock market; Textual analysis; Stock links

JEL Classification: G11, G12, G14

Suggested Citation

Ge, Shuyi and Li, Shaoran and Li, Xinping and Yan, Xianglong and Zheng, Hanyu, CSNCD: China Stock News Co-mention Dataset (November 11, 2023). Available at SSRN: https://ssrn.com/abstract=4629877 or http://dx.doi.org/10.2139/ssrn.4629877

Shuyi Ge

Nankai University - Department of Finance ( email )

94 Weijin Road
Tianjin, 300071
China

Shaoran Li (Contact Author)

Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, 100871
China

Xinping Li

Peking University - School of Economics ( email )

Yiheyuan Road
the school of economics builiding
Beijing, 000000
China

Xianglong Yan

Peking University - School of Economics ( email )

Yiheyuan Road
the school of economics builiding
BEIJING, 000000
China

Hanyu Zheng

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

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