全球智库信息集成服务系统(G2TT): DP15682 Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media

G2TT

来源类型	Discussion paper
规范类型	论文
来源ID	DP15682
	DP15682 Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media
	Marlene Amstad; Leonardo Gambacorta; Chao He; Fan Dora XIA
发表日期	2021-01-18
出版年	2021
语种	英语
摘要	Trade tensions between China and US have played an important role in swinging global stock markets but effects are difficult to quantify. We develop a novel trade sentiment index (TSI) based on textual analysis and machine learning applied on a big data pool that assesses the positive or negative tone of the Chinese media coverage, and evaluates its capacity to explain the behaviour of 60 global equity markets. We find the TSI to contribute around 10% of model capacity to explain the stock price variability from January 2018 to June 2019 in countries that are more exposed to the China-US value chain. Most of the contribution is given by the tone extracted from social media (9%), while that obtained from traditional media explains only a modest part of stock price variability (1%). No equity market benefits from the China-US trade war, and Asian markets tend to be more negatively affected. In particular, we find that sectors most affected by tariffs such as information technology related ones are particularly sensitive to the tone in trade tension.
主题	Financial Economics
关键词	Stock returns Trade Sentiment Big data Neural network Machine learning
URL	https://cepr.org/publications/dp15682
来源智库	Centre for Economic Policy Research (United Kingdom)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/544691
推荐引用方式 GB/T 7714	Marlene Amstad,Leonardo Gambacorta,Chao He,et al. DP15682 Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media. 2021.