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Abstract

With the China’s emergence in the global economy, the United States has faced a widening trade deficit with China, which led to a very unbalanced trade relationship. Acrimonious differences concerning the “fairness” of the two sides’ industry subsidies triggered the U.S.-China trade conflict (trade war) through the action of both countries levying extreme unilateral tariffs. The trade war has affected both the values of the import and export goods produced by firms and also have caused investors to lose confidence, thus inducing economic the panic that is reflected in price fluctuations in related stock markets. That is, U.S. and China stock markets may be sensitive to media news on the trade war, as reports of policy announcements result in corrections to investors’ market expectations. Thus, this research aims to reveal whether media news’ coverage of the U.S.-China trade conflicts predicts the two countries’ daily stock returns. We find that US-China trade news could increase two-day-ahead stock return in China, whereas the same news would decrease four-day-ahead stock return in US. The opposite effects imply that U.S. investors react pessimistically to news in a free and open market economic system, while Chinese investors are more optimistic about the news in a socialist market economic system with beliefs in their more powerful government.

Keywords: Media news, U.S.-China trade conflicts, U.S. stock returns, Chinese stock returns, Cable News Network (CNN), Economic Daily News, Straits Times of Singapore, British Broadcasting Corporation (BBC).

JEL Classification: F13; G15.

Received: 15 February 2021 / Revised: 19 March 2021 / Accepted: 21 April 2021/ Published: 12 May 2021

Contribution/ Originality

The paper's primary contribution is finding that US-China trade news increases two-day-ahead stock return in China, whereas the same news decreases four-day-ahead stock return in US. It may imply U.S. investors react pessimistically in a free and open economic system, while Chinese investors are more optimistic in a socialist market.

1. INTRODUCTION

With the China’s emergence in the global economy, the United States has faced a widening trade deficit with China, which led to a very unbalanced trade relationship. The rapid growth of the U.S. bilateral trade deficit with China hit to the highest level on record in 2017. In February of the same (2017) year, the annual losses in the United States due to counterfeit goods, pirated software, and theft of trade secrets are between $225 billion and $600 billion according to a survey conducted by the Commission on the Theft of American Intellectual Property.¹ United States President Trump therefore accused China of infringement and damage to American companies. He has imposed high punitive tariffs and took restrictions on goods from China to export to the U.S. because of the unfair trade practices of China, which violated section 301 of the U.S. Trade Act. China’s response was to counter with similar retaliatory measures, imposing high tariffs on goods imported from the United States. Although the total amount of goods involved is not as large as the scale of China’s exports to the United States, it focused specifically on the main exports of the United States, that of agriculture products. Acrimonious differences concerning the “fairness” of the two sides’ industry subsidies triggered the U.S.-China trade conflict (trade war) through the action of both countries levying extreme unilateral tariffs. Affected by the high tariffs imposed by both sides, the trade volume between China and the United States has shrunk sharply and damaged their GDP along with that of the rest of the world. China also retreated to now becoming the third largest trading partner of the United States, which is the first time that China lost out to Mexico since 2005. The negative impact and the uncertainty resulting from the U.S.-China trade conflicts on the overall economy and corporate profits have sharply increased stock price volatility, but the responses of equity markets to news releases on the trade war have yet to be empirically examined. Thus, this study explores the possible correlation between the U.S.-China trade conflicts and the two countries’ stock markets based on data with a timeline mark of news media and stock market returns.

The current trade war has affected both the values of the import and export goods produced by firms and also has caused investors to lose confidence, thus inducing economic the panic, that is reflected in price fluctuations in related stock markets. For example, on March 1, 2018, U.S. President Trump announced plans to impose tariffs of 25% on steel imports and 10% on imported aluminum, which caused the U.S. stock markets to fall sharply while Asian markets also take fright. ² We find that U.S. and China stock markets are sensitive to media news on the trade war, as reports of policy announcements result in corrections to investors’ market expectations.

Stock market volatility reflects investors’ confidence and beliefs on financial markets, which generally are derived from media news reports. Several studies have demonstrated that textual analysis of news may improve the accuracy of forecasted returns in stock markets (Kothari, Li, & Short, 2009; Loughran & McDonald, 2011; Tetlock, 2007). Peress (2014) stated that stock return volatility is significantly affected by news, suggesting that the media contribute to stock market efficiency. Fang and Peress (2009) studied the relationship between media reports and stocks’ cross-sectional returns, finding that stocks with low media attention have a significant premium. Niederhoffer (1971) analyzed news headlines published by the New York Times and noted that the stock market reacted most strongly on the first day after major news was released. Zhao, Zhao, Yang, Wang, and Li (2012) utilized the linear regression method and found that the stocks of small-cap companies are more strongly affected by news reports, and the duration is longer.

In terms of policy uncertainty and the financial market, Baker, Bloom, and Davis (2016) used keywords in the news to create an Economic Policy Uncertainty (EPU) index that measures research policy uncertainty, presenting that policy uncertainty has a significant impact on stock price fluctuations. Hu, Kutan, and Sun (2018) showed U.S. EPU has negative effects on Chinese stock returns with a lag of one week. Due to the possible spillover risk from trade policy uncertainty upon the financial system, He, Lucey, and Wang (2020) found that such uncertainty from U.S.-China trade conflicts has heterogeneous effects on the two countries’ stock markets - that is, the impact is positive on the U.S. stock market, but negative on the China stock market. However, previous studies generally used monthly data, which cannot capture an immediate impact on the market when the policy is released. Thus, given the critical time point of policy announcements, this study aims to reveal whether the media news on the U.S.-China trade conflicts predict daily market returns in the two countries. In an era of advanced information technology, most investors usually get information on international trends through news media based in their own country. However, the attention that media around the world place on events is not always the same, and the angle of interpretation on the same news event varies. For example, China Briefing News (in China) mentioned that the Ministry of Commerce of China announced to conduct anti-dumping and countervailing investigations against sorghum imported from the United States on February 4, 2018. This news was not reported by Reuters (in the U.S.). Likewise, news about imposing a 25% tariff on approximately US$50 billion worth of Chinese imports announced by Trump was highlighted by Reuters, but China Briefing News did not report it. Moreover, differences in cultural background and language use between China and the United States plus the different positions of the media when reporting news in different countries have led to different reports and information received by investors in China and the United States, which in turn influence investors’ perception of an international situation. Thus, the news sources on the U.S.-China trade conflicts that we consider in this study include Cable News Network (CNN) of the United States, Economic Daily News of Taiwan, the Straits Times of Singapore, and the British Broadcasting Corporation (BBC).

In order to find a possible relationship of media news on this trade war and stock returns, we use the following stock indices of the U.S. and China to calculate market returns: Dow Jones Industrial Average, S&P 500, NASDAQ, Shanghai A Share, Shanghai Composite, and Shenzhen a Share. According to our best knowledge, there appears to be scant literature investigating news on the U.S.-China trade war and how it might predict stock returns.

According the empirical results, we find that U.S.-China trade conflict news releases from CNN increase Chinese stock returns with a two-day lag by about 0.5% to 0.7%, while the same news decreases U.S. stock returns by about 0.3% to 0.4% with a four-day lag. This implies that U.S. investors react pessimistically to news in a free and open market economic system, while Chinese investors are more optimistic about the same news, which may be due to their powerful government in a socialist market economic system and the triumphant nationality of Chinese society. That is, they believe their powerful government would not lose in the trade war. The remainder of the paper is organized as follows. Section 2 reviews the related literature. Section 3 describes the data and constructs the empirical model. Section 4 presents the empirical results. Section 5 draws conclusions.

2. DATA, HYPOTHESES, AND EMPIRICAL APPROACHES

2.1. Data

In order to find the possible relationship in media news on U.S.-China trade conflicts and stock returns, we use the following indices of the U.S. and China to calculate returns:  Shanghai A Share, Shanghai Composite, Shenzhen A Share, S&P 500, Dow Jones Industrial Average, and NASDAQ. We collect data on a daily basis for these indices from Investing.com, spanning February 14, 2017 to February 12, 2020.
We consider four news media outlets to record the time point of the U.S.-China trade conflict news events. The first one is Cable News Network (CNN) in the United States.³ CNN provides news 24 hours a day and has 90.1 million television households as subscribers (97.7% of households with cable) in the United States as of September 2018. ⁴ Since there are no timeline data of U.S.-China trade conflicts news from China’s official news media, we use Taiwan media, which has a similar social background, and Singapore media as representatives of Asian news media. Thus, the second one that we use to record the time point of trade war news events is Economic Daily News,⁵ which only reports financial and economic issues. The Straits Times of Singapore is the third media. Finally, we also use the timeline from the British Broadcasting Corporation (BBC),⁶ which is the world’s oldest national media company.⁷ Table 1 shows the statistics of U.S. and Chinese stock returns. The average index returns of the three China markets are negative, while the average stock returns of the U.S. markets are positive. The market with the largest standard deviation for returns is Shenzhen A Share, while it also has the lowest rate of return. NASDAQ has the maximum rate of return.

Table-1. Statistics of U.S. and Chinese stock returns.

Market Returns	Obs	Mean	Std. Dev.	Min	Max
Shanghai A	1,094	-0.0003	0.0108	-0.0772	0.0560
Shanghai composite	1,094	-0.0001	0.0110	-0.0772	0.0560
Shenzhen A	1,094	-0.0003	0.0138	-0.0901	0.0542
S&P 500	1,094	0.0006	0.0082	-0.0410	0.0496
Dow Jones	1,094	0.0006	0.0084	-0.0460	0.0498
NASDAQ	1,094	0.0006	0.0103	-0.0443	0.0584

Table 2 lists the correlation of the news media. The correction between different media is positive, but not high, especially for the relationship of BBC with the other media. This may imply that news media have different timeline marks for the U.S.- China trade conflicts, which may be due to different concerns of their readership.

Table-2. Correlation of news media.

	CNN	Economic Daily News	Straits Times	BBC
CNN	1
Economic Daily News	0.2346	1
Straits Times	0.2524	0.2685	1
BBC	0.0750	0.1310	0.1552	1

2.2. Hypotheses’ Development

Hypothesis 1: The influence of U.S.-China trade conflict news events from the media runs in opposite direction for U.S. and Chinese stock returns. American investors may react pessimistically to news in a free and open market economic system, while Chinese investors may be more optimistic about news due to their belief in their powerful government in a socialist market economic system. Moreover, U.S.-China trade conflicts may spur Chinese nationalism with more confidence of winning the trade war.

Hypothesis 2: The influence of U.S.-China trade conflict news events from the media negatively impacts U.S. and Chinese stock returns. Since trade friction intensifies via imposing heavy tariffs on each other’s goods, there is no winner in this U.S.-China trade war.

2.3. Empirical Approach

We test the hypotheses by the following regression model:

Moreover, we adopt the Newey-West standard errors to eliminate potential heterogeneity and autocorrelation problems (Newey & West, 1987).

3. EMPIRICAL RESULTS

3.1. Timeline from CNN News

In order to understand the possible relationship of U.S.-China trade conflict news events on U.S. and Chinese stock returns, we use the following regression model to examine the time point of the events on CNN News:

The number in the parentheses is the Newey-West standard error (Newey & West, 1987). The sample period runs from February 14, 2017 to February 12, 2020. *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

Table-3. CNN News’ Impact on U.S. and Chinese stock returns.

In Table 3, the coefficient (B1) of the U.S.-China trade conflict news events from CNN in Model (1), Model (2), and  Model (3) is positive, but insignificant. The coefficient (B2) of the U.S.-China trade conflict news events from CNN in Model (1), Model (2), and Model (3) is positive and significant at the 0.05 level, implying that such news releases increase Chinese stock returns with a two-day lag by about 0.5% to 0.7%, including Shanghai A Share, Shanghai Composite, and Shenzhen A Share. In other words, the releases of U.S.-China trade conflict news could increase two-day-ahead stock return in China.

In terms of U.S. stock returns in Model (4), Model (5), and Model (6), the coefficient (B4) shows a significantly negative influence. It suggests that U.S.-China trade conflict news releases from CNN have a negative relationship with U.S. stock returns, decreasing them by about 0.3% to 0.4% with a four-day lag.

According to the results of Table 3 we observe that not only can U.S.-China trade conflict news events be used to forecast U.S. and China daily stock market returns, but that the directions of the relationship between news and stock returns are also opposite. These opposite impacts between U.S. and Chinese stock returns support our Hypothesis 1. In other words, U.S. investors react pessimistically to such news, while Chinese investors are more optimistic about the news. This may be due to their different market economic systems (free and open market economy and socialist market economy, respectively) and their different cultures.

3.2. Timeline from Economic Daily News

In this section we run the following regression model based on the news from the Economic Daily News (Taiwan) as representative of news headlines from Asia:

Table-4. Economy Daily News’ Impact on U.S. and Chinese stock returns.

3.3. Timeline from Straits Times News

In terms of the other news media in Asia, we evaluate the Straits Times of Singapore and its influences of U.S.-China trade conflicts news on U.S. and Chinese stock returns according to the following regression model:

The number in the parentheses is the Newey-West standard error (Newey & West, 1987). The sample period runs from February 14, 2017 to February 12, 2020. *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.  The results appear in Table 5.

From the statistical significance of results in Models (1), (2), and (3) of Table 5, U.S.-China trade conflicts news increases Chinese stock returns by about 6%-9% with a two-day lag after the news release. The results are consistent with our findings in the previous section. On the other hand, the coefficients in Models (4), (5), and (6) are all insignificant, implying that the effects of such news on U.S. stock returns do not exist. In other words, U.S.-China trade conflict news and U.S. stock returns do not have any statistically significant relationship.

Table-5. Straits Times News’ Impact on U.S. and Chinese stock returns.

3.4. Timeline from BBC News

In addition to U.S. or China news sources, we also consider the BBC News (UK) to run the following regression model:

The number in the parentheses is the Newey-West standard error (Newey & West, 1987). The sample period runs from February 14, 2017 to February 12, 2020. *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.  The results appear in Table 6.

Table 6 shows the results regarding the possible influence of U.S.-China trade conflicts news as recorded by the BBC on U.S. and Chinese stock returns. In Table 6 we find that the coefficients of the U.S.-China trade conflict news events, no matter on the returns of Dow Jones Industrial Average, S&P 500, NASDAQ, Shanghai A Share, Shanghai Composite Index, or Shenzhen A Share, are all insignificant. In other words, there is no statistically significant evidence that news from the BBC may or may not affect U.S. and Chinese stock returns.

Table-6. BBC News’ Impact on U.S. and Chinese stock returns.

4. CONCLUSION

Acrimonious differences concerning the “fairness” of subsidies have triggered the U.S.-China trade war through the action of extreme unilateral tariffs being levied. The trade war not only affects the values of import and export goods produced by firms around the world, but also causes investors to lose confidence and induces panic over the economy, as reflected in severe price fluctuations in global stock markets. Thus, given the critical time point of related news releases, this study reveals whether media outlets’ news of U.S.-China trade conflicts predict daily U.S. and Chinese stock returns.

According to our empirical results, we observe that U.S.-China trade conflict news releases from CNN can forecast U.S. and China daily stock market returns, but the directions of the relationship between news and stock returns are opposite. News events could increase two-day-ahead stock return in China by about 0.5% to 0.7% and decrease four-day-ahead stock return in US by about 0.3% to 0.4%. This suggests U.S. investors react pessimistically to news in a free and open market economic system, while Chinese investors are more optimistic about related news events, which may be due to their powerful government in a socialist market economic system and the triumphant nationality of Chinese society. The results are consistent if we use news events from the Economic Daily News (Taiwan) and the Straits Times (Singapore). However, the impacts of U.S.-China trade conflict news from the BBC (UK), no matter on the returns of Dow Jones Industrial Average, S&P 500, NASDAQ, Shanghai A Share, Shanghai Composite, or Shenzhen A Share, are all insignificant. However, we do not distinguish whether information in the news has a positive or negative effect on U.S. and China economic development. In the future, one may be able to deal with this through a text mining method. Moreover, there are many sources of news in addition to mainstream news media, such as social media, like Facebook and Twitter. They may also have possible influences that would be valuable to examine in this context.

Funding: This study received no specific financial support.

Competing Interests: The author declares that there are no conflicts of interests regarding the publication of this paper.

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Footnotes