stock market volatility
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The paper aims to examine the nonlinear asymmetric relationship among the implied volatility indices of the Indian stock market, gold, and oil for the period from 2nd March 2009 to 29th October 2021. Nonlinear Autoregressive Distributed Lag (NARDL) model results provide evidence of asymmetric nonlinear relationship among the selected variables in the short-run and the long-run. The positive and negative shocks to gold and oil implied volatility indices have a positive and significant influence on the implied volatility of the Indian stock market. The expected volatility of gold has a short-term symmetric impact on expected stock market volatility in the short run. Whereas, the implied volatility of oil has a long-run asymmetric impact on the implied volatility of the stock market. Increasing volatility in oil prices can be viewed as a signal for the starting point for the volatility of the Indian stock markets. In the long run, positive shocks to gold volatility have more impact on the expected volatility of the Indian stock market than the negative. This indicates that investors are shifting their investments from gold to stocks for higher returns when the gold prices are fluctuating.


2022 ◽  
Vol 59 ◽  
pp. 101517
Author(s):  
Fernando Díaz ◽  
Pablo A. Henríquez ◽  
Diego Winkelried

2022 ◽  
pp. 204-230
Author(s):  
Ezaz Ahmed ◽  
Md. Mahadi Hasan ◽  
Zakir Hossen Shaikh ◽  
Mohammad Irfan

Researchers examine stock volatility in emerging (E7) nations prior to and during COVID-19 announcements using multiple volatility estimations. The correlation coefficient matrix indicates that there is a strong positive correlation between the specified volatility estimators in the pre-COVID-19 and post-COVID-19 periods. Rogers-Satchell standard deviation has the first rank, and Garman-Klass has the last position in the pre-post-COVID-19 analysis volatility estimators. However, the authors discover a considerable influence of pre-post COVID-19 on the world's E7 countries. The findings' primary implication is that post-COVID-19 volatility is greater than pre-COVID-19 volatility. This means that investors' financial portfolios should be rebalanced to favor industries that are less impacted by COVID-19. Additionally, it serves as an early warning signal for investors and the government to take preventative measures in the event that it occurs again in the future.


2022 ◽  
Vol 20 (1) ◽  
pp. 1
Author(s):  
Yu Ting Mai ◽  
Yi Hsien Wang ◽  
Kuang Hsun Shih ◽  
Fu Ju Yang

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Raphael Kuranchie-Pong ◽  
Joseph Ato Forson

PurposeThe paper tests the overconfidence bias and volatility on the Ghana Stock Exchange (GSE) during the pre-Covid-19 pandemic and Covid-19 pandemic period.Design/methodology/approachThe study employs pairwise Granger causality to test the presence of overconfidence bias on the Ghana stock market as well as GARCH (1,1) and GJR-GARCH (1, 1) models to understand whether overconfidence bias contributed to volatility during pre-Covid-19 pandemic and Covid-19 pandemic period. The pre-Covid-19 pandemic period spans from January, 2019 to December, 2019, and Covid-19 pandemic period spans from January, 2020 to December, 2020.FindingsThe paper finds a unidirectional Granger causality running from weekly market returns to weekly trading volume during the Covid-19 pandemic period. These results indicate the presence of overconfidence bias on the Ghana stock market during the Covid-19 pandemic period. Finally, the conditional variance estimation results showed that excessive trading of overconfident market players significantly contributes to the weekly volatility observed during the Covid-19 pandemic period.Research limitations/implicationsThe empirical findings demonstrate that market participants on the GSE exhibit conditional irrationality in their investment decisions during the Covid-19 pandemic period. This implies investors overreact to private information and underreact to available public information and as a result become overconfident in their investment decisions.Practical implicationsFindings from this paper show that there is evidence of overconfidence bias among market players on the GSE. Therefore, investors, financial advisors and other market players should be educated on overconfidence bias and its negative effect on their investment decisions so as to minimize it, especially during the pandemic period.Originality/valueThis study is a maiden one that underscores investors’ overconfidence bias in the wake of a pandemic in the Ghanaian stock market. It is a precursor to the overconfidence bias discourse and encourages the testing of other behavioral biases aside what is understudied during the Covid-19 pandemic period in Ghana.


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