How COVID-19 has affected stock market persistence? Evidence from the G7’s

Bentes, Sónia R.

doi:10.1016/j.physa.2021.126210

Cited by 23 publications

(8 citation statements)

References 58 publications

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“…We also find a significant impact of adverse events such as the COVID-19 pandemic financial crisis and the Russo-Ukrainian War on spillovers across markets. The high spillover effects among cryptocurrencies, stocks, and commodities during our sampling period of 2020–2022 are consistent with previous empirical studies that document significant contagion across financial markets since the start of the COVID-19 pandemic in 2020 (Ghosh et al 2022 ; Carporale et al 2022 ; Vera-Valdés 2022 ; Adekoya 2022 ; Hui and Chan 2022 ; Shahzad et al 2021a ; Shahzad et al 2021b ; Bentes 2021 ; Youssef et al 2021 ; Yousaf and Ali 2020 ). Our study contributes to the extant body of literature on the matter by documenting the relationship between cryptocurrencies and other financial markets at higher-order moments.…”

Section: Empirical Analysissupporting

confidence: 89%

“…Our results also show that short-term volatility connectedness tends to be greater than long-term volatility connectedness, except during the first year of the COVID-19 pandemic in 2020. These results suggest a higher level of shock persistence among markets at the beginning of the pandemic (Adekoya 2022 ; Vera-Valdés 2022 ; Carporale et al 2022 ; Bentes 2021 ; Youssef et al 2021 ; Shahzad et al 2021a ).…”

Section: Empirical Analysismentioning

confidence: 91%

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Dynamic connectedness and network in the high moments of cryptocurrency, stock, and commodity markets

Hanif

Pham

et al. 2023

Financ Innov

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This study examines the connectedness in high-order moments between cryptocurrency, major stock (U.S., U.K., Eurozone, and Japan), and commodity (gold and oil) markets. Using intraday data from 2020 to 2022 and the time and frequency connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Econom 16(2):271–296, 2018), we investigate spillovers among the markets in realized volatility, the jump component of realized volatility, realized skewness, and realized kurtosis. These higher-order moments allow us to identify the unique characteristics of financial returns, such as asymmetry and fat tails, thereby capturing various market risks such as downside risk and tail risk. Our results show that the cryptocurrency, stock, and commodity markets are highly connected in terms of volatility and in the jump component of volatility, while their connectedness in skewness and kurtosis is smaller. Moreover, jump and volatility connectedness are more persistent than that of skewness and kurtosis connectedness. Our rolling-window analysis of the connectedness models shows that connectedness varies over time across all moments, and tends to increase during periods of high uncertainty. Finally, we show the potential of gold and oil as hedging and safe-haven investments for other markets given that they are the least connected to other markets across all moments and investment horizons. Our findings provide useful information for designing effective portfolio management and cryptocurrency regulations.

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Section: Empirical Analysissupporting

confidence: 89%

Section: Empirical Analysismentioning

confidence: 91%

Dynamic connectedness and network in the high moments of cryptocurrency, stock, and commodity markets

Hanif

Pham

et al. 2023

Financ Innov

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“…In contrast, the research study developed by Bentes (2021) showed evidence on how the FIGARCH model worked well for all G7 markets by following the d component for the FIGARCH boundaries 0 < d < 1. Our research differentiates from Bentes (2021) study as our boundaries align with those of Härdle and Mungo (2007) boundaries for the FIGARCH; the d component must be positive and equal to or below 0.5.…”

Section: Discussionmentioning

confidence: 89%

Financial Uncertainty from a Dual Shock at Global Level–Insights from Kuwait

Alotaibi

Morales

2022

IJFS

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Global stock markets experienced a dual shock in 2020 due to the impact of the global health crisis, parallel to a simultaneous shock derived from the Saudi Arabia and Russia oil price war. The dual shock fueled oil market volatility with lasting effects as the global economy is immersed in an energy crisis combined with high inflationary pressures exacerbated by heightened energy costs. This research paper implemented GARCH and FIGARCH models on daily returns from 31 December 2015, to 9 December 2021, to examine volatility persistence and long memory processes. The world’s most prominent economies are represented by the G7, E7 and the GCC stock markets. Particular attention was devoted to the case of Kuwait as an example of a small oil-dependent economy. The research findings suggest evidence of volatility persistence across the markets, as reported by the GARCH (1,1) model. The FIGARCH (1,1) did not offer significant evidence of long memory processes except for the cases of FTSE 100, BIST 100, IDEX, BSE 100 and Bahrain.

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“…The GARCH model can extract the weight and direction of linkages between markets. Therefore, GARCH family methods are widely used in the research of co-movement between markets [20] , [21] .…”

Section: Introductionmentioning

confidence: 99%