ABSTRACT
The spreading COVID-19 outbreak has wreaked havoc on the world's financial system that raises an urgent need for the re-evaluation of the gold as safe haven for their money because of the unprecedented challenges faced by markets during this period. Therefore, the current study investigates whether different asset class volatility indices affect desirability of gold as a safe-haven commodity during COVID-19 pandemic. Long run and the short run relationship of gold prices with gold price volatility, oil price volatility, silver price volatility and COVID-19 (measured by the number of deaths due to COVID) has been analyzed in the current study by applying ARDL Bound testing cointegration and non linear ARDL approach on daily time series data ranging from January 2020 to Dec 2021. Findings of the study suggest that in the long run, oil price volatility and gold price volatility positively affect the gold prices, whereas the effect of silver price volatility on gold prices is negative in the long run. However in the short run, all the three indices negatively impact the gold prices. In contrast, the impact of COVID-19 is positive both in the short run and in the long run that proves the validity of gold as safe haven asset in the time of the deadly pandemic. The findings of this study have significant implications and offer investors with some indications to hedge their investments by considering the gold's ability of safe haven during this era of pandemic.
ABSTRACT
The COVID-19 pandemic has imposed significant challenges on education worldwide, particularly in areas with limited online teaching experience. The research design is based on constructivism learning theory and the technology acceptance model. A questionnaire was also distributed to a university of finance and economics in China. Structural equation model was used to test the influence mechanism of social media interaction on college students' willingness to use e-learning platform continuously. The positive moderating effect of online teaching context on this mechanism is further analyzed. Therefore, the use of social media in the online teaching process in higher education institutions should be encouraged, and a good online teaching context should be fostered.
ABSTRACT
The objective of this study is to investigate the impact of the COVID-19 pandemic and stock market psychology on investor investment decisions in different business units operating in the Shandong stock market. The sample size of the study consists of 5,000 individuals from six different business units. The study used the event study statistical technique to analyze the market reaction to newly released information from the stock market perspective to assess whether the number of COVID-19 positive cases impacted it. With a Z score value of 40.345 and a P-value of 0.000, the Wilcoxon test indicated that stock prices before and after the pandemic were quite different. The test showed a positive relationship between the pandemic and the stock market. Further, the results indicated that COVID-19 and stock market psychology had a significant positive impact on investor investment decisions in cosmetic and beauty, consumer household, textiles and apparel, and consumer electronics industries; however, in the sporting and consumer appliance industries, it had an insignificant negative impact. This study serves to guide investors to make suitable changes in their stock market trading practices to counter these challenges to increase their required rate of return from their specific stock market investment. The findings have important insights for various stakeholders including governments, regulatory bodies, practitioners, academia, industry, and researchers.
ABSTRACT
This study aims to investigate the influence of psychological biases on the investment decision of Chinese individual investors after the pandemic of COVID-19 with a moderating role of information availability. A cross-sectional method with a quantitative research approach was employed to investigate the hypothesized relationships among variables. The snowball sampling technique was applied to collect the data through a survey questionnaire from individual investors investing in the Chinese stock market. Smart-PLS statistical software was used to analyze the data and for the estimation of hypotheses. Results indicated that overconfidence, representative bias, and anchoring bias have a significant and positive influence on investment decisions during the post-Covid-19 pandemic;however, the availability bias has insignificant and negative effects on the investment decision during the post-COVID-19 pandemic. Moreover, findings indicated that information availability has a significant moderating role in the relationship of psychological biases with the investment decision during the post-COVID-19 pandemic. This study contributes to the body of knowledge regarding behavior finance, psychological biases, and investment decision in emerging stock markets. The findings of the present study improve the understanding that how investors’ psychology affects their investment decisions.
ABSTRACT
Among the climate change policies, improving energy efficiency and investment in renewable sources are considered key driving forces that may lead to sustainable outcomes over a longer period. This study aims to provide new insight into the role of green financing, volatility, and geopolitical risk in dealing with the investment in renewable energy sources through micro and macro-level data during 2015–2020 in China. Several benchmarks and other regression estimation approaches were applied to address the study title while considering both direct and indirect association between the variables of interest. The study findings have shown that green financing (in the form of green bonds) and green regulations like environmental taxes play a significant and positive role in promoting investment in renewable energy sources. However, oil price volatility and geopolitical risk adversely impact the investment pattern for the clean energy sources in China when controlling the firm size and corporate governance practices. The study also justifies the moderating role of green regulations while strengthening the relationship between green financing and investment in renewable energy. Based on the study findings, it is recommended that green firms in China should be promoted so that investment in renewable energy sources would be considered as a long-term strategy. Comprehending both theoretical and empirical findings, the study has provided meaningful insights for policymakers and environmentalists to design and implement environmental practices that have sustainable returns.
ABSTRACT
Mitigation measures and control strategies relating to the novel coronavirus disease 2019 (COVID-19) have been widely applied in many countries to reduce the transmission of this pandemic disease. China was the first country to implement a strong lockdown policy to control COVID-19 when countries worldwide were struggling to manage COVID-19 cases. However, lockdown causes numerous changes to air-quality patterns due to the low amount of traffic and the decreased human mobility it results in. To study the impact of the strict control measures of the new COVID-19 epidemic on the air quality of Hubei in early 2020, the air-quality monitoring data of Hubei’s four cities, namely Huangshi, Yichang, Jingzhou, and Wuhan, from 2019 to 2021, specifically 1 January to 30 August, was examined to analyze the characteristics of the temporal and spatial distribution. All air-quality pollutants decreased during the active-COVID-19 period, with a maximum decrease of 26% observed in PM10, followed by 23% of PM2.5, and a minimum decrease of 5% observed in O3. Changes in air pollutants from 2017 to 2021 were also compared, and a decrease in all pollutants through to 2020 was found. The air-quality index (AQI) recorded an increase of 2% post-COVID-19, which shows that air quality will worsen in future, but it decreased by 22% during the active-COVID-19 period. A path analysis model was developed to further understand the relationship between the AQI and air-quality patterns. This path analysis shows a strong correlation between the AQI and PM10 and PM2.5, however its correlation with other air pollutants is weak. Regression analysis shows a similar pattern of there being a strong relationship between AQI and PM10 (r2 = 0.97) and PM2.5 (r2 = 0.93). Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, it is likely that the reduction in air pollution and the significant improvement in ambient air quality due to lockdowns provided substantial short-term health benefits. The government must implement policies to control the environmental issues which are causing poor air quality in post-COVID-19.