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Ok Google What Is The Stock Market Doing Right Now
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Submission date: July 3, 2020 / Revision date: August 12, 2020 / Acceptance date: August 14, 2020 / Publication date: August 17, 2020
This study examined the early impact of COVID-19 sentiment on the U.S. economy. that. Stock market using big data. This study uses data from the Daily News Sentiment Index (DNSI) and Google Trends on coronavirus-related searches to assess sentiment toward the coronavirus and United States (US) stocks for the period ending January 21. We examine the market’s relationship with 11 selected sectoral indices. From 2020 to May 20, 2020. Extensive research on sentiment analysis to predict stock market movements uses Twitter data, but less so data from DNSI and Google Trends. Additionally, this study investigates whether changes in DNSI predict economic crisis in the United States. Excess returns are obtained from Fama-French’s three-factor model. The results of this study provide a comprehensive overview of the early impact of COVID-19 sentiment in the United States. .
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The COVID-19 pandemic is one of the most economically costly pandemics in recent history. The current coronavirus pandemic is fundamentally different from previous outbreaks, such as SARS in 2003 and Ebola from 2014 to 2016. Coronaviruses are transmitting at a much faster rate globally due to closer international integration and the possibility of transmission by asymptomatic carriers. As the coronavirus disease (COVID-19) spreads rapidly around the world, many people are becoming more aware of the news and are increasingly searching for coronavirus on Google. Coronavirus news and Google searches play an important role in keeping people informed about the current state of the crisis and influencing investors’ decisions in the stock market. Therefore, news and Google searches regarding the coronavirus can affect stock market sentiment and asset prices. Once the COVID-19 pandemic ends, new asset management methods will be required, and short-term, nimble investment decisions are expected to become preferred.
It is widely recognized that stock market investors need high quality data to make informed decisions. Particularly during market crises, investors need technology to obtain timely and accurate data. Using high-quality data, investors can perform faster analysis and decision-making in the asset management process, allowing them to quickly respond to volatile market conditions. Positive or negative public sentiment related to a stock market crisis can have a ripple effect on investors’ decisions in the stock market. By combining available information about the stock market with real-time big data from non-traditional sources such as news sentiment data and Google Trends data, we can analyze the uneven impact of the COVID-19 shock and investor growth. You can further improve your understanding of capabilities. . Appropriate response. Real-time big data can also help overcome the limitations of official data, such as low quality, limited coverage, and sometimes significant reporting delays.
To maintain a competitive advantage during market crises, stock market investors not only need to understand the nature of market crises, such as timing, strength, and volatility, but also to realize positive returns and It also requires strategic investment decisions that can minimize losses arising from a crisis. applause. When a shock has a significant impact on the stock market, investors analyze past months of data to find potential lessons from the market crisis and develop indicators to respond quickly and intelligently to market volatility. . Investors can then better protect their portfolios should market shocks occur again. Many previous studies have conducted sentiment analysis, which uses big data such as tweeter data and other social media data to predict stock market movements [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21].
This study aims to explore the early impact of COVID-19 sentiment on the United States. that. Stock market by industry using big data. The coronavirus disease (COVID-19) outbreak has affected nearly every industry and sector around the world, but with nationally imposed curfews and other social distancing measures, leisure It is clear that consumer spending in sectors such as the industry and hospitality has fallen dramatically. For this reason, the degree of impact caused by the sentiment of the new coronavirus infection is expected to differ depending on the industry. Therefore, we examine the correlation between COVID-19 sentiment and 11 selected US sector indices. that. stock market. Sentiment regarding COVID-19 is measured by big data from the Daily News Sentiment Index (DNSI) and Google Trends for coronavirus-related searches. DNSI is a high-frequency measure of economic sentiment based on lexical analysis of economic news articles from 16 major U.S. companies. that. newspaper. Specifically, the study examined DNSI and Google searches for five terms related to the coronavirus and the economy in the United States. “Coronavirus”, “testing”, “unemployment”, “recession”, “vaccine”, etc. Next, this study examines the significance of the relationship between COVID-19 sentiment and 11 selected sectoral indices in the United States. that. The stock market provides a comprehensive overview of the initial impact of COVID-19 sentiment on the US. Furthermore, by visualizing changes in the degree of correlation due to time differences, we propose strategic investment plans that take time differences into account. Additionally, this study examines whether changes in DNSI predict the impact of the United States. Excess returns are obtained from his three-factor model of Fama-French.
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This study is at the forefront of research on the relationship between COVID-19 sentiment and the U.S. economy. that. stock market. Since the ongoing coronavirus disease (COVID-19) pandemic was confirmed to have reached the United States. that. As of January 2020, there is little research on the impact of COVID-19 on the United States. that. stock market. Extensive research on sentiment analysis to predict stock market movements uses Twitter data, but less so data from DNSI and Google Trends. To our knowledge, this study is the first to examine the early impact of COVID-19 sentiment on the United States using DNSI or Google Trends data. that. Stock market by industry.
The rest of this document is organized as follows. Section 2 discusses prior research on stock market sentiment analysis. Section 3 presents the data and methods of the analysis. Experimental results are presented and discussed in detail in Section 4. The final results are presented in Section 5.
Sentiment analysis is widely used in many applications such as product recommendation, healthcare, policy, and surveillance [22]. People’s emotions related to emotions, attitudes, emotions, and opinions expressed in large amounts of social media data have been shown to play an important role in measuring investor opinions [13]. Tetlock [19] systematically investigated the interaction between media content and stock market activity using the daily content of his Wall Street Journal columns from 1984 to 1999. They showed that news media content predicts market price and trading volume movements. Further supporting Tetlock’s evidence [19], Garcia [8] found that the predictability of stock returns by news content was concentrated during recessions. They used some of the positive and negative words in his two New York Times economic news columns as a proxy for national sentiment.
In addition to studies using news media content from popular newspapers, a number of studies have also used social media data for sentiment analysis to predict stock market movements. The most well-known work in this area is by Bollen et al. [3]. They used Twitter data to see if the public’s collective mood correlated with the Dow Jones Industrial Average.
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