Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Asymmetric dependence between stock market returns and news during COVID-19 financial turmoil.

ABSTRACT: •I investigate the stock market's reaction to coronavirus news in the top six most affected countries by the pandemic.•The fake news exerts a negative nonlinear influence on the inferior and the middle quantiles throughout the distribution of returns.•The media coverage leads to a decrease in returns across middle and superior quantiles and has no effects on the inferior ones.•During COVID19 turmoil superior quantiles of returns distribution exhibit negative dependence on past performances, while inferior and middle quantiles are not affected by this phenomenon.•The gold return has a positive correlation with the stock markets, which amplifies during extreme bearish and bullish periods indicating that it does not behave as a "Safe Havens" asset.

SUBMITTER: Cepoi CO

PROVIDER: S-EPMC7299872 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Asymmetric dependence between stock market returns and news during COVID-19 financial turmoil.

Cepoi Cosmin-Octavian CO

Finance research letters 20200618

•I investigate the stock market's reaction to coronavirus news in the top six most affected countries by the pandemic.•The fake news exerts a negative nonlinear influence on the inferior and the middle quantiles throughout the distribution of returns.•The media coverage leads to a decrease in returns across middle and superior quantiles and has no effects on the inferior ones.•During COVID19 turmoil superior quantiles of returns distribution exhibit negative dependence on past performances, whil ...[more]

PMID: 32837370

Similar Datasets

Does non-fundamental news related to COVID-19 matter for stock returns? Evidence from Shanghai stock market.

Project description:The COVID-19 outbreak generates various types of news that affect economic and financial systems. No studies have assessed the effects of such news on financial markets. This study sheds light on the impact of non-fundamental news related to the COVID-19 pandemic on the liquidity and returns volatility. Because we examined extreme events, we performed quantile regression on daily data from December 31, 2019 to the end of lockdown restrictions in China on April 7, 2020. Results showed that the non-fundamental news, as the number of deaths and cases related to the COVID-19, raised the stock market returns volatility and reduced the level of stock market liquidity, increasing overall risk, whereas fundamental macroeconomic news remained largely immaterial for the stock market. These findings are explained by a knock-on effect because the health system's inability to manage and treat a high number of COVID-19 patients in intensive care led the country to implement a lockdown and the global economy to largely shut down.

| S-EPMC9756967 | biostudies-literature

Quantifying the relationship between financial news and the stock market.

Project description:The complex behavior of financial markets emerges from decisions made by many traders. Here, we exploit a large corpus of daily print issues of the Financial Times from 2(nd) January 2007 until 31(st) December 2012 to quantify the relationship between decisions taken in financial markets and developments in financial news. We find a positive correlation between the daily number of mentions of a company in the Financial Times and the daily transaction volume of a company's stock both on the day before the news is released, and on the same day as the news is released. Our results provide quantitative support for the suggestion that movements in financial markets and movements in financial news are intrinsically interlinked.

| S-EPMC3868958 | biostudies-literature

Machine learning sentiment analysis, COVID-19 news and stock market reactions.

Project description:The recent COVID-19 pandemic represents an unprecedented worldwide event to study the influence of related news on the financial markets, especially during the early stage of the pandemic when information on the new threat came rapidly and was complex for investors to process. In this paper, we investigate whether the flow of news on COVID-19 had an impact on forming market expectations. We analyze 203,886 online articles dealing with COVID-19 and published on three news platforms (MarketWatch.com, NYTimes.com, and Reuters.com) in the period from January to June 2020. Using machine learning techniques, we extract the news sentiment through a financial market-adapted BERT model that enables recognizing the context of each word in a given item. Our results show that there is a statistically significant and positive relationship between sentiment scores and S&P 500 market. Furthermore, we provide evidence that sentiment components and news categories on NYTimes.com were differently related to market returns.

| S-EPMC9842392 | biostudies-literature

Project description:We investigate a novel dataset of more than half a million 15 second transcribed audio snippets containing COVID-19 mentions from major US TV stations throughout 2020. Using the Latent Dirichlet Allocation (LDA), an unsupervised machine learning algorithm, we identify seven COVID-19 related topics discussed in US TV news. We find that several topics identified by the LDA predict significant and economically meaningful market reactions in the next day, even after controlling for the general TV tone derived from a field-specific COVID-19 tone dictionary. Our results suggest that COVID-19 related TV content had nonnegligible effects on financial markets during the pandemic.

| S-EPMC9721134 | biostudies-literature

COVID-19 pandemic effect on trading and returns: Evidence from the Chinese stock market.

Project description:Using a daily foreign and institution flows data, this paper studies how institutional and foreign investors respond to the COVID-19 pandemic events in China. The results indicate that during the COVID-19 crisis foreign investors play a market stabilization role showing significant negative feedback trading, whereas institution investors do not stabilize the market. And compared to the pre-COVID-19 period, foreign investors even exhibit stronger negative feedback trading. Further analyses confirm that foreign investors' negative feedback is mainly driven by their response to negative returns. Moreover, both institutional and foreign investors' trading show stronger forecastability of future returns during the pandemic period. And the negative returns after foreigners' selling and positive returns after institutional buying are much stronger during the crisis period.

| S-EPMC9188298 | biostudies-literature

Market framing bias and cross-sectional stock returns

Project description:This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.

| S-EPMC10468084 | biostudies-literature

Nonlinear nexus between cryptocurrency returns and COVID-19 COVID-19 news sentiment.

Project description:The paper examines how various COVID-19 COVID-19 news sentiments differentially impact the behaviour of cryptocurrency returns. We used a nonlinear technique of transfer entropy to investigate the relationship between the top 30 cryptocurrencies by market capitalisation and COVID-19 COVID-19 news sentiment. Results show that COVID-19 COVID-19 news sentiment influences cryptocurrency returns. The nexus is unidirectional from news sentiment to cryptocurrency returns, in contrast to past findings. These results have practical implications for policymakers and market participants in understanding cryptocurrency market dynamics under extremely stressful market conditions. .

| S-EPMC9434911 | biostudies-literature

Investor attention on COVID-19 and African stock returns.

Project description:We examine the financial consequences of rising global investor attention or risk attitude related to the COVID-19 pandemic for African stock markets. Using daily investor attention indices, which are based on global COVD-19-related google search queries, and stock return indices for 14 African stock markets, we show that investor attention is an important determinant of stock returns. Our estimates suggest that an increase in investor attention consistently reduces stock returns in three stock markets, namely Botswana, Nigeria, and Zambia. In contrast, an increase in investor attention may enhance stock returns in Ghana and Tanzania. Our estimates imply that, in uncertain times like the current pandemic, stock markets like those of Ghana and Tanzania may offer potential diversification benefits to investors. We demonstrate that our estimates are broadly robust using a composite measure of investor attention.•We built a direct and unambiguous measure of investor attention or risk attitude related to the COVID-19 pandemic.•In an exponential generalised autoregressive heteroskedasticity of order one (i.e. EGARCH(1,1)) framework, we regressed stock returns on their first lags, investor attention, exchange rate returns, and commodity returns, and controlled for investor attention in the variance equation.

| S-EPMC8374205 | biostudies-literature

COVID-19 lockdowns, stimulus packages, travel bans, and stock returns.

Project description:This paper examines the effect of government responses of G7 countries to the coronavirus pandemic (COVID-19) on stock market returns. Using time-series data, we show that lockdowns, travel bans, and economic stimulus packages all had a positive effect on the G7 stock markets. However, lockdowns were most effective in cushioning the effects of COVID-19. Our results are robust to different measures of returns and controls for other factors of returns.

| S-EPMC7440077 | biostudies-literature

Dataset on share issuance, abnormal returns and market timing in the Brazilian stock market.

Project description:This article presents a dataset to investigate the determinants of firms' decision for primary share issuance and the effects of market timing on primary share issues in the Brazilian stock market. The data refer to Brazilian nonfinancial firms that issued primary shares (IPOs and SEOs) in the 2004-2015 period. The data were gathered from the online bases of Economatica® and the São Paulo Securities, Commodities and Futures Exchange (BM&FBovespa). The final sample was composed of 123 firms and 165 primary share issues: 97 initial public offerings and 68 follow-on offerings. The dataset was developed to support a model that captures market timing behavior through cumulative abnormal returns and shows the effects of this behavior on the amount of proceeds raised. The dataset contains subsamples and different analysis time windows, processed and unprocessed data. Researchers can use the dataset for future research and comparisons with other markets and models. The related research article using part of the current dataset was published under the following title: "Effects of market timing on primary share issues in the Brazilian capital market" (Gomes et al.).

| S-EPMC6661535 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data