Market sentiment to COVID‐19 and the Chinese stock market

We classify the market sentiment to COVID‐19 into expected and unexpected components and then examine their particular impacts on the stock market. We find that unexpected sentiment causes fluctuations in the stock market more than expected sentiment does. However, unexpected sentiment cannot affect stock market informativeness despite the remarkable informational effect of expected sentiment. Moreover, the relation between expected sentiment and stock market fluctuation or informativeness is one‐way, whereas there exists a two‐way interaction between unexpected sentiment and stock market fluctuation. This further confirms that expected sentiment is informational, whereas unexpected sentiment is quite noisy and informationally harmful.

The policy response to COVID-19 pandemic and its impact on the equity market sentiment: The Indian experience.

We examine the dynamics of the impact of the evolving policy response during the COVID-19 pandemic on the equity market sentiment in India. We operationalise our study by examining the India VIX, the fear gauge of the Indian equity market as an indicator for the market sentiment, and the country level Government Response Index of the Blavatnik School of Government, Oxford University as an indicator for the policy response. The relation is examined through the Markov-switching model using high-frequency daily data from January 30, 2020, to May 31, 2021. The evidence suggests that the policy response has a positive impact on the market sentiment when the market is fearful. Further, the evidence suggests that both the high-fear state and the low-fear state of the market sentiment given by the model are short-lived indicating heightened volatility and possible speculation during the ongoing pandemic in the Indian equity market.

Financial market sentiment and stock return during the COVID-19 pandemic.

Using 1,287,932 pieces of textual data from news media, we measure the financial market sentiment worldwide. We conduct the first international study of the effect of the financial market sentiment on stock return during the COVID-19 pandemic. Results show that the intensification of the epidemic adversely affects the stock market, but the increasing financial market sentiment increases the stock market return, even during the worst of the pandemic. Our results remain robust using alternative proxies. Additional analysis suggests that negative sentiment has a more significant impact on stock market returns than positive sentiment. Taken together, our findings confirm that negative financial market sentiment amplifies the impact of the crisis on the stock market, and positive financial market sentiment can help mitigate the losses caused by the shock.

Market sentiment to COVID ‐19 and the Chinese stock market

We classify the market sentiment to COVID-19 into expected and unexpected components and then examine their particular impacts on the stock market. We find that unexpected sentiment causes fluctuations in the stock market more than expected sentiment does. However, unexpected sentiment cannot affect stock market informativeness despite the remarkable informational effect of expected sentiment. Moreover, the relation between expected sentiment and stock market fluctuation or informativeness is one-way, whereas there exists a two-way interaction between unexpected sentiment and stock market fluctuation. This further confirms that expected sentiment is informational, whereas unexpected sentiment is quite noisy and informationally harmful.

The Impacts of The Systematic, Idiosyncratic Risks and Market Sentiment on China A-Shares Performances

The purposes of this paper are (i) to examine 3 driving factors affecting China A-shares market performance;namely systematic risk, idiosyncratic risk, and market sentiment, and (ii) to investigate the relationship between state-owned enterprise (SOE) & non-SOE and stock returns. In addition, the study also analyze normal condition and the impacts of Sino-US trade war and Covid-19 pandemic. This study employs monthly data which is divided into two parts namely (i) 2004-2020 period and (ii) 2018-2020 period. Multiple classic asset pricing models are employed to investigate the impacts of the 3 driving factors on stock returns. The results showed that these 3 driving factors exert significant influence on China A-shares in 2004-2020, However, the impact of market sentiment is weak during the period 2018-2020. Furthermore, market risks, firm size and B/M factor show great impacts on both SOE and non-SOE, profitability factor affecting non-SOE stock return is more important than investment which improves SOE stock return. This study proposes that investors and companies pay more attention to systematic risk and idiosyncratic risk, which potentially have greater impact on the stock market and to reduce unnecessary economic losses © International Journal of Economics and Management

Investor Sentiment and Stock Market Reactions to COVID-19: Evidence from China

This paper treats the outbreak of coronavirus disease 2019 (COVID-19) as a natural experiment that can provide insights into the effects of investor sentiment on stock market reactions. Employing the event study methodology (ESM) and taking the date of the Wuhan lockdown as the event date, we find that average abnormal return (AAR) and cumulative abnormal return (CAR) are significantly negative, and average trading volume excesses far more than before within two days of the outbreak. Further, we establish a difference-in-differences (DID) model to investigate the differences between Hubei and non-Hubei listed companies. The results show that for Hubei listed companies, the change of excessive trading volume (ETV) between pre-event and post-event period is significantly higher than that of non-Hubei listed companies, while there exhibits no relationship between the change of AAR and registration place. Overall, our findings provide new evidence for the interaction of local bias and investor sentiment affecting stock market reactions. [ FROM AUTHOR] Copyright of Discrete Dynamics in Nature & Society is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Can news-based economic sentiment predict bubbles in precious metal markets?

This study examines the role of market sentiment in predicting the price bubbles of four strategic metal commodities (gold, silver, palladium, and platinum) from January 1985 to August 2020. It is the first to investigate this topic using sentiment indices, including news-based economic and consumer-based sentiments developed using different methods. We observed the role of sentiment as a reliable indicator of future bubbles for some metal commodities and found that bubbles were regularly concomitant with bearish sentiments for gold and platinum. Moreover, gold and palladium were the only commodities that experienced a bubble during the COVID-19 pandemic. Overall, our findings suggest inclusion of sentiment to the model that predicts the price bubbles of precious metals.

Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?

We use a consumption based asset pricing model to show that the predictability of excess returns on risky assets can arise from only two sources: (1) stochastic volatility of fundamental variables, or (2) departures from rational expectations that give rise to predictable investor forecast errors and market inefficiency. While controlling for stochastic volatility, we find that a variable which measures non-fundamental noise in the Treasury yield curve helps to predict 1-month-ahead excess stock returns, but only during sample periods that include the Great Recession. For these sample periods, higher noise predicts lower excess stock returns, implying that a shortage of arbitrage capital in financial markets allowed excess returns to drop below the levels justified by fundamentals. The statistical significance of the predictor variables that control for stochastic volatility are also typically sensitive to the sample period. Measures of implied and realized stock return variance cease to be signficant when the COVID-influenced data from early 2020 onward is included.

US biopharmaceutical companies' stock market reaction to the COVID-19 pandemic. Understanding the concept of the 'paradoxical spiral' from a sustainability perspective.

In an uncertain and finite world, actions towards the development of a green economy are attracting wider support. The damaging anthropogenic impact on earth systems is leading humanity to devastating situations, jeopardizing its very survival. A new world scenario has emerged with COVID-19, where the biopharmaceutical sector has arisen as a powerful effective solution for the health, economic and social crisis derived from the pandemic. This research aims to study the stock market reaction of the two US biopharmaceutical companies that first developed messenger RNA vaccines against COVID-19 (Pfizer and Moderna), considering two time periods, before and during COVID. In the analysis, the influence of the technological market index, market volatility, and investor sentiment are also considered. The results show an unequal influence of market volatility and market sentiment on the returns of both companies, as well as a different volatility behaviour. Furthermore, a contagion effect is observed during the COVID period between both companies and the technological market. The study's findings provide investors, organizations, policy-makers and society with useful information for the design of policies and strategies that ultimately are called to ensure sustainable growth for future generations.