Bitcoin and CEE stock markets: fresh evidence from using the DECO-GARCH model and quantile on quantile regression

Hung, Ngo Thai

doi:10.1108/ejmbe-06-2020-0169

Cited by 9 publications

(6 citation statements)

References 39 publications

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“…Financial markets have made significant progress in terms of volume and magnitude in recent years, thanks to the emergence of a wide range of cryptocurrencies and various innovative financial instruments. This remarkable development in financial markets has also increased risk and compelled global investors to seek out a safe haven investment (Hung, 2021b). Bitcoin, which captures public interest, is the well-known currency in virtual financial asset markets.…”

Section: Introductionmentioning

confidence: 99%

Asymmetric connectedness among S&P 500, crude oil, gold and Bitcoin

Hung

2022

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PurposeThis paper investigates the dynamic intercorrelation among cryptocurrency (Bitcoin) and conventional financial assets (gold, oil and S&P 500).Design/methodology/approachThe dynamic contemporaneous nexus has been analyzed using spillover index developed and extended by Diebold and Yilmaz (2012, 2014) and Kyrtsou-Labys (2006) nonlinear causality tests. This study is implemented using the daily data spanning from January 2013 to December 2021.FindingsFirst, using the spillover index, the authors find evidence that the S&P 500 was a net transmitter of volatility from oil and gold markets, but a net receiver of volatility from Bitcoin. Return spillovers from crude oil were transmitted first to gold, and Bitcoin markets and return spillovers from gold were transmitted to Bitcoin. Second, Kyrtsou-Labys nonlinear causality tests provide us further insights into the lead-lag interconnections among the four key considered variables from the economic perspective. Specifically, a close inspection of these empirical results, the integration of the four key assets is significant. Similarly, price fluctuation dependency among Bitcoin, stock, gold and oil markets is generally minimal, but it strengthens throughout the COVID-19 period.Originality/valueThis paper is the first study employing the spillover index Diebold-Yilmaz alongside with Kyrtsou-Labys nonlinear causality tests not only to capture the directional return spillover effects but also to highlight the potential presence of asymmetric causality relationships, nonlinear effects among assets under investigation that the previous studies have been ignored in these relations. Therefore, the main contribution of this article to the related literature in this field is significant.

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Section: Introductionmentioning

confidence: 99%

Asymmetric connectedness among S&P 500, crude oil, gold and Bitcoin

Hung

2022

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“…The second series of research looked at how businesses reacted to COVID-19 (see also, Didier et al, 2021;Gu et al, 2020;Meyer et al, 2021). COVID-19's influence on other aspects of the financial system is the subject of the third set of research (see Adam et al, 2022;Agyei et al, 2021;Asafo-Adjei et al, 2021;Boateng et al, 2021;Cox et al, 2020;Liu et al, 2020;Mazur et al, 2021;Owusu Junior et al, 2021;Zeren and Hizarci, 2020;Hung, 2021). The results from the empirical literature have been largely varying across markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Asymmetric information flow to G7 and Nordic equities markets during COVID-19 pandemic

Owusu

Hung

2023

JRF

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PurposeThis paper investigates the probable differential impact of the confirmed cases of COVID-19 on the equities markets of G7 and Nordic countries to ascertain possible interdependencies, diversification and safe haven prospects in the era of the COVID-19 pandemic over the short-, intermediate- and long-term horizons.Design/methodology/approachThe authors apply a unique methodology in a denoised frequency-domain entropy paradigm to the selected equities markets (Li et al. 2020).FindingsThe authors’ findings reinforce the operability of the entrenched market dynamics in the COVID-19 pandemic era. The authors divulge that different approaches to fighting the pandemic do not necessarily drive a change in the deep-rooted fundamentals of the equities market, specifically for the studied markets. Except for an extreme case nearing the end (start) of the short-term (intermediate-term) between Iceland and either Denmark or the US equities, there exists no potential for diversification across the studied markets, which could be ascribed to the degree of integration between these markets.Practical implicationsThe authors’ findings suggest that politicians should pay closer attention to stock market fluctuations as well as the count of confirmed COVID-19 cases in their respective countries since these could cause changes to market dynamics in the short-term through investor sentiments.Originality/valueThe authors measure the flow of information from COVID-19 to G7 and Nordic equities using the entropy methodology induced by the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), which is a data-driven technique. The authors employ a larger sample period as a result of this, which is required to better comprehend the subtleties of investor behaviour within and among economies – G7 and Nordic geographical blocs – which largely employed different approaches to fighting the COVID-19 pandemic. The authors’ focus is on diverging time horizons, and the ICEEMDAN-based entropy would enable us to measure the amount of information conveyed to account for large tails in these nations' equity returns. Furthermore, the authors use a unique type of entropy known as Rényi entropy, which uses suitable weights to discern tailed distributions. The Shannon entropy does not account for the fact that financial assets have fat tails. In a pandemic like COVID-19, these fat tails are very strong, and they must be accounted for.

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“… Hung (2021) found that Bitcoin has an average positive correlation with the stock market of CEE (Croatia, Hungary, Poland, Romania, and the Czech Republic), using the Dynamic Equi-correlation GARCH (DECO-GARCH) model. Omane-Adjepong et al.…”

Section: Content Analysismentioning

confidence: 99%

“…This part will discuss some of their findings. Hung (2021) found that Bitcoin has an average positive correlation with the stock market of CEE (Croatia, Hungary, Poland, Romania, and the Czech Republic), using the Dynamic Equi-correlation GARCH (DECO-GARCH) model. Omane-Adjepong et al ( 2021) found an asymmetric herd behaviour in the cryptocurrency and stock markets of 10 emerging economies within G20 conducting the cross-sectional absolute deviation (CSAD) approach.…”

Section: Othersmentioning

confidence: 99%