Showing papers on "Stock (geology) published in 2021"
TL;DR: The pandemic-induced drop in stock returns was milder among firms with stronger pre-2020 finances, and firms controlled by families, large corporations, and governments performed better, and those with greater ownership by hedge funds and other asset management companies performed worse.
456 citations
TL;DR: It is found that natural gas, food, healthcare, and software stocks earn high positive returns, whereas equity values in petroleum, real estate, entertainment, and hospitality sectors fall dramatically, and loser stocks exhibit extreme asymmetric volatility that correlates negatively with stock returns.
438 citations
TL;DR: Using time-series data, it is shown that lockdowns, travel bans, and economic stimulus packages all had a positive effect on the G7 stock markets, but lockdowns were most effective in cushioning the effects of COVID-19.
266 citations
TL;DR: A fractal contagion effect of the COVID-19 pandemic on the stock markets fizzles out over time (in the middle and long run) for both the stock Markets return and volatility.
221 citations
TL;DR: In this article, the effect of COVID-19 on U.S. restaurant firms' stock returns varies according to the firms' pre-pandemic characteristics by employing three firm-level dimensions (financial conditions, corporate strategies, and ownership structure).
162 citations
TL;DR: In this article, the authors study the short-term market reactions of US and European stocks during the beginning of the COVID-19 pandemic and find that stocks react significantly negatively to the announcement of the first death in a given country.
153 citations
TL;DR: In this paper, the authors analyzed the return and volatility spillover between the COVID-19 pandemic in 2020, the crude oil market, and the stock market by employing two empirical methods for connectedness.
145 citations
TL;DR: The empirical results show that, up to 24-month lag, infectious disease pandemic has significant positive impacts on the permanent volatility of international stock markets, even after controlling the influences of past realized volatility, global economic policy uncertainty and the volatility leverage effect.
143 citations
TL;DR: In this paper, the effects of the COVID-19 outbreak and its following lockdown on daily stock returns in Vietnam, a fast-growing emerging market that successfully revived after the pandemic lockdown, were explored.
Abstract: This study explores the effects of the COVID-19 outbreak and its following lockdown on daily stock returns in Vietnam, a fast-growing emerging market that successfully revived after the pandemic lockdown.,This study uses panel-data regression models to evaluate the influence of the daily increase in the number of COVID-19 confirmed cases during pre-lockdown and lockdown on daily stock returns of 723 listed firms in Vietnam from 30 January to 30 May 2020.,The study confirms the adverse impact of the daily increasing number of COVID-19 cases on stock returns in Vietnam. The study also discloses that the Vietnam stock market before and during the nationwide lockdown performed in opposing ways. Though COVID-19 pre-lockdown had a significant, negative impact on Vietnam's stock returns, the lockdown period had a significant, positive influence on stock performance of the entire market and the different business sectors in Vietnam. The financial sector was hardest hit on the Vietnam stock market during the COVID-19 outbreak.,The study indicates investors' confidence and trust in the Vietnam government's decisions to combat COVID-19 and favorable stocks prices were the main reasons that the Vietnam stock market rebounded during and after lockdown.,This is the first study to examine the impact of COVID-19 during the pre-lockdown and lockdown periods on stock performance in Vietnam, a rapidly developing economy that was successful in controlling the pandemic with a rejuvenated stock market after lockdown.
126 citations
TL;DR: Compared with other methods, the CNN-BiLSTM-AM method is more suitable for the prediction of stock price and for providing a reliable way for investors’ to make stock investment decisions.
Abstract: In recent years, with the rapid development of the economy, more and more people begin to invest into the stock market. Accurately predicting the change of stock price can reduce the investment risk of stock investors and effectively improve the investment return. Due to the volatility characteristics of the stock market, stock price prediction is often a nonlinear time series prediction. Stock price is affected by many factors. It is difficult to predict through a simple model. Therefore, this paper proposes a CNN-BiLSTM-AM method to predict the stock closing price of the next day. This method is composed of convolutional neural networks (CNN), bi-directional long short-term Memory (BiLSTM), and attention mechanism (AM). CNN is used to extract the features of the input data. BiLSTM uses the extracted feature data to predict stock closing price of the next day. AM is used to capture the influence of feature states on the stock closing price at different times in the past to improve the prediction accuracy. In order to prove the effectiveness of this method, this method and other seven methods are used to predict the stock closing price of the next day for 1000 trading days of the Shanghai Composite Index. The results show that the performance of this method is the best, MAE and RMSE are the smallest (which are 21.952 and 31.694). R2 is the largest (its value is 0.9804). Compared with other methods, the CNN-BiLSTM-AM method is more suitable for the prediction of stock price and for providing a reliable way for investors’ to make stock investment decisions.
125 citations
TL;DR: In this article, the authors investigate if trust affects global stock market volatility during the COVID-19 pandemic, using a sample of 47 national stock markets, and find the stock markets' volatility to be significantly lower in high-trust countries.
TL;DR: Wang et al. as discussed by the authors found that stock prices in China have become as informative about future profits as they are in the US, and this rise in stock price informativeness has coincided with an increase in investment efficiency among privately owned firms.
TL;DR: In this paper, the authors employed a quantile-based regression approach to examine the relationship between crude oil and renewable energy stock prices under average conditions, and found that the lagged effect of WTI oil returns on clean energy stock returns is generally significant.
TL;DR: In this paper, a trivariate VAR-BEKK-GARCH model was used to investigate the dynamic relationship among the Chinese stock market, commodity markets and global oil price.
TL;DR: In this article, the authors examined the effect of the global pandemic on stock market volatility and whether economic strength, measured by a set of selected country-level economic characteristics and factors such as economic resilience, intensity of capitalism, level of corporate governance, financial development, monetary policy rate and quality of health system, could potentially mitigate the possible detrimental effect of global pandamine on stock price volatility.
TL;DR: In this paper, the authors examined the impacts of the 2019-nCoV outbreak on the global stock markets using a sample of 49 stock market indices of the developed and emerging markets in the world using the standard event methodology.
TL;DR: This article showed that market risks associated with global oil and stock markets can be effectively hedged by gold during this COVID-19 pandemic period, while there is evidence of time-variation and regime changes, as the hedging potentials seem to be stronger at higher oil prices.
TL;DR: Using high-frequency daily data across 53 emerging and 23 developed countries from January 14 to August 20, 2020, it is found that COVID-19 cases and deaths adversely affect stock returns and increase volatility and trading volume.
TL;DR: The authors found that the decline in stock market returns in response to one percent increase in growth in confirmed cases is stronger for the countries with higher national-level uncertainty aversion, which indicates that the national level uncertainty avoidance, which determines how sensitive members of a nation are to uncertainty, moderates the stock markets' reaction to the pandemic.
TL;DR: In this article, the authors investigated the dynamic connectedness between stock indices and the effect of economic policy uncertainty (EPU) in eight countries where COVID-19 was most widespread (China, Italy, France, Germany, Spain, Russia, the US, and the UK) by implementing the time-varying VAR (TVP-VAR) model for daily data over the period spanning from 1/01/2015 to 05/18/2020.
Abstract: This study investigates the dynamic connectedness between stock indices and the effect of economic policy uncertainty (EPU) in eight countries where COVID-19 was most widespread (China, Italy, France, Germany, Spain, Russia, the US, and the UK) by implementing the time-varying VAR (TVP-VAR) model for daily data over the period spanning from 01/01/2015 to 05/18/2020. Results showed that stock markets were highly connected during the entire period, but the dynamic spillovers reached unprecedented heights during the COVID-19 pandemic in the first quarter of 2020. Moreover, we found that the European stock markets (except Italy) transmitted more spillovers to all other stock markets than they received, primarily during the COVID-19 outbreak. Further analysis using a nonlinear framework showed that the dynamic connectedness was more pronounced for negative than for positive returns. Also, findings showed that the direction of the EPU effect on net connectedness changed during the pandemic onset, indicating that information spillovers from a given market may signal either good or bad news for other markets, depending on the prevailing economic situation. These results have important implications for individual investors, portfolio managers, policymakers, investment banks, and central banks.
TL;DR: In this article, the influence of financial innovation by fintech brokerages on individual investors' trading and stock prices was studied using data from Robinhood, and they found that Robinhood investors engage in more attention-induced trading than other retail investors.
Abstract: We study the influence of financial innovation by fintech brokerages on individual investors’ trading and stock prices. Using data from Robinhood, we find that Robinhood investors engage in more attention-induced trading than other retail investors. For example, Robinhood outages disproportionately reduce trading in high-attention stocks. While this evidence is consistent with Robinhood attracting relatively inexperienced investors, we show that it can also be partially driven by the app’s unique features. Consistent with models of attention-induced trading, intense buying by Robinhood users forecast negative returns. Average 20-day abnormal returns are -4.7% for the top stocks purchased each day.
TL;DR: In this paper, the authors investigated the impact of financial stress on clean energy stock returns against changes in oil prices, gold prices, and financial stress in the US and European economies by applying Quantile Autoregressive Distributed Lag approach.
01 Jan 2021
TL;DR: In this paper, the impact of macro economic factors on stock price of Vingroup (VIC), a big Vietnam real estate firm, in the context Viet Nam and the US economies receive impacts from global economic crisis.
Abstract: After the global economic crisis 2007–2011 and the recent post-low inflation 2014–2015, Viet Nam economies, its financial and stock market as well as real estate market experienced indirect and direct impacts on their operation, system and stock price. Although some economists have done researches on the relationship among macro economic factors such as: consumer price index (CPI), inflation, GDP…, this paper aims to consider the interaction between macro economic factors such as Viet Nam inflation and GDP growth rate, US inflation, exchange rate, risk free rate and other macro factors, and esp. their impacts on stock price of Vingroup (VIC), a big Vietnam real estate firm, in the context Viet Nam and the US economies receive impacts from global economic crisis. This is one main objective of this research paper. This research paper finds out VIC stock price has a negative correlation with risk free rate in VN and deposit rate of VN commercial banks, but has a positive correlation with lending rate in Vietnam. And the statistical analysis will generate results which help us to suggest macro policies in favor of the local stock and financial market. Real estate industrial risk over years has been affected much by macro economic risk, credit risk, and legal risk; therefore, government bodies need to issue proper macro economic legal, financial and credit policies in order to stimulate, develop stock market and reduce workload pressure for Vietnam bank system.
TL;DR: Wang et al. as discussed by the authors investigated the impact of COVID-19 on Chinese stock market by an event study and examined the effect of individual investor sentiment on returns, showing a stronger positive correlation between individual investor sentiments and stock returns than usual.
TL;DR: This paper found that stock markets in countries with lower individualism and higher uncertainty avoidance experienced larger declines and greater volatilities during the first three weeks after a country's first COVID-19 case announcement.
Journal Article•
TL;DR: In this article, the authors employed a quantile-based regression approach to examine the relationship between crude oil and renewable energy stock prices under average conditions, and found that the lagged effect of WTI oil returns on clean energy stock returns is generally significant.
Abstract: Unlike previous studies examining the association between crude oil and renewable energy stock prices under average conditions, we employ a quantile-based regression approach offering a more comprehensive dependence structure under diverse market conditions. Using weekly data covering crude oil prices (WTI market) and three clean energy stock indices (the Wilderhill Energy Index, MAC Global Solar Energy Index, and S&P Global Clean Energy Index), quantile regression analyses provide solid evidence of the decreasing dependence of clean energy stock returns on crude oil returns. The lagged effect of WTI oil returns on clean energy stock returns is generally significant, which indicates that clean energy stock returns react differently to new information on oil returns under different market conditions. We further check for asymmetrical effects of oil returns on clean energy stock returns in various market conditions and find a strong effect of negative oil returns during bearish periods and an insignificant effect during bullish episodes.
TL;DR: In this paper, the stock price crash risk for firms searched for more via Google before its withdrawal subsequently increases by 19%, suggesting that Internet searching facilitates investors' information processing, and the sensitivity of stock returns to negative Internet posts also rises by 36%.
TL;DR: In this paper, the authors examined the behavior of cryptocurrencies and stock markets during the COVID-19 pandemic through the wavelet coherence approach and Markov switching autoregressive model.
TL;DR: In this article, the authors examined the risk contagion among international stock markets during the COVID-19 pandemic by using the realized volatility information from sixteen major stock markets in the world.
TL;DR: In this paper, the authors mount an investigation on how COVID-19 has impacted the Australian stock market returns and find that COVID has had a dramatic effect on global stock markets.
Abstract: Coronavirus pandemic (COVID-19) has had a dramatic effect on global stock markets. In this article, we mount an investigation on how COVID-19 has impacted the Australian stock market returns. Using...