Impact on Stock Market across Covid-19 Outbreak

This paper analysis the impact of pandemic over the global stock exchange. The stock listing values are determined by variety of factors including the seasonal changes, catastrophic calamities, pandemic, fiscal year change and many more. This paper significantly provides analysis on the variation of listing price over the world-wide outbreak of novel corona virus. The key reason to imply upon this outbreak was to provide notion on underlying regulation of stock exchanges. Daily closing prices of the stock indices from January 2017 to January 2022 has been utilized for the analysis. The predominant feature of the research is to analyse the fact that does global economy downfall impacts the financial stock exchange. Keywords: Stock Exchange, Matplotlib, Streamlit, Data Science, Web scrapping.

Evidence of Economic Policy Uncertainty and COVID-19 Pandemic on Global Stock Returns

This paper examines the impact of changes in economic policy uncertainty (EPU) and COVID-19 shock on stock returns. Tests of 16 global stock market indices, using monthly data from January 1990 to August 2021, suggest a negative relation between the stock return and a country’s EPU. Evidence suggests that a rise in the U.S. EPU causes not only a decline in a country’s stock return, but also a negative spillover effect on the global market; however, we cannot find a comparable negative effect from global EPU to U.S. stocks. Evidence suggests that the COVID-19 pandemic has a negative impact that significantly affects stock return worldwide. This study also finds an indirect COVID-19 impact that runs through a change in domestic EPU and, in turn, affects stock return. Evidence shows significant COVID-19 effects that change relative stock returns between the U.S. and global markets, creating a decoupling phenomenon.

Good news reduces trust in government and its efficacy: The case of the Pfizer/BioNTech vaccine announcement

The announcement of Pfizer/BioNTech’s COVID-19 vaccine success on November 9, 2020 led to a global stock market surge. But how did the general public respond to such good news? We leverage the unexpected vaccine announcement to assess the effect of good news on citizens’ government evaluations, anxiety, beliefs and elicited behaviors in the US and the UK. While most outcomes were unaffected by the news, trust in government and elected politicians (and their competency) saw a significant decline in both countries. As the news did not concern the governments, and the governments did not have time to act on the news, our results suggest that the decline of trust is more likely explained by the psychological impact of good news on reasoning style. In particular, we suggest two possible styles of reasoning that might explain our results: a form of motivated reasoning and a reasoning heuristic of relative comparison.

Impact of commodities and global stock prices on the idiosyncratic risk of Bitcoin during the COVID-19 pandemic

In times of exogenous systemic shocks, such as the COVID-19 pandemic, it is important to identify hedge or safe haven assets. Therefore, this paper analyzes changes in the idiosyncratic risk of Bitcoin in a portfolio of commodities and global stocks. For this purpose, the M-GARCH model employed considers the interdependence among all the portfolio assets by using a time-varying asset pricing framework. This framework measures the impact of commodities and global stock prices as sources of systemic risk for Bitcoin returns before and after the COVID-19 pandemic. The evidence suggests that during the COVID-19 pandemic, the effects of changes in commodities and global prices on the idiosyncratic risk of Bitcoin were statistically significant. The idiosyncratic risk of Bitcoin measured as a percentage of total variance not accounted for by the proposed model rose from 86.06% to 95.05% during the pandemic. These results are in line with previous studies regarding the properties of Bitcoin as a hedge or safe haven asset for a portfolio composed of commodities and global stocks.

Maritime Stock Prices and Information Flows: A Cointegration Study

In this study, the issue of how global maritime stock prices influence the stock prices of large transportation companies in the U.S. and other large markets is examined. Maritime stocks are chosen because they are central in global trade and thus may be good indicators of future global stock market and economic trends. Maritime companies are often owned by families or governments and are traded in stock markets with lower standards of accountability, hence information flows from maritime stocks may be slower than flows from other stocks. Cointegration and vector error-correction analysis is used to analyze the short-term and long-term relationships between maritime stocks, rail stocks, and trucking stocks. Evidence is found of a gradual diffusion of information from maritime stock prices to large rail or trucking stocks. This suggests that price changes in maritime stocks may help predict changes in prices in non-maritime transportation stocks.

The 1987 Stock Exchange Crash in Historical Perspective

This chapter aims to explore the different facets of the collective memory of the 1987 Crash in the US, which represented an unprecedented collapse of prices on the global stock markets. The 22.3% fall of the Dow Jones on Black Monday (19 October 1987) represents the biggest single-day stock market collapse in history—even greater than that of 24 October 1929. The crash spread to other major financial markets over the world, but was quickly resolved thanks to the central banks’ intervention on the capital markets. In the context of Reaganomics, the crash can be seen as the first financial crisis of the second globalization wave in the strictest sense of the term ‘financial’, without taking into consideration the banking crises of the 1970s and the debt crisis in the early 1980s. However, unlike other financial crises, memories of this market break remained either vague or inexistent in public opinion, or fragmented and partial for economists and historians—until the subprime crisis. Since then, the 1987 warning and the potential dangers of uncontrolled markets were brought to light. The final lesson to be learned from this example of an evolving memory is about using the past.