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1 – 5 of 5Parichat Sinlapates and Surachai Chancharat
This paper aims to investigate the effects of volatility transmission among Bitcoin and other leading cryptocurrencies, namely, Binance USD, BNB, Cardano, Dogecoin, Ethereum…
Abstract
Purpose
This paper aims to investigate the effects of volatility transmission among Bitcoin and other leading cryptocurrencies, namely, Binance USD, BNB, Cardano, Dogecoin, Ethereum, Polkadot, Polygon, Solana, Tether, USD Coin and XRP.
Design/methodology/approach
The multivariate BEKK-GARCH model is used with the daily data set from 1 January 2017 to 31 March 2023. The data set is analysed in its entirety and is also the COVID-19 epidemic period.
Findings
The study reveals that while the volatility of cryptocurrency prices is influenced by their own historical shocks and volatility, there is proof of the effects shock transmission among Bitcoin and other notable cryptocurrencies. Furthermore, the authors identify the spillover effects of volatility among all 11 pairs and provide evidence that conditional correlations with varying time constants are present, and predominantly positive for both the entire and COVID-19 outbreak periods.
Practical implications
The findings will be helpful to market experts who want to avoid losses in traditional assets. To develop the best risk management and hedging strategies, businesses might use the information to build asset portfolios or personalise payment methods. The use of such data by investors and portfolio managers could aid in the development of investment opportunities, risk insurance plans or hedging strategies for the management of financial portfolios.
Originality/value
To the best of the authors’ knowledge, the use of the BEKK-GARCH model for examining the effects of volatility spillover among Bitcoin and the other eleven top cryptocurrencies has not been previously documented.
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Florin Aliu, Alban Asllani and Simona Hašková
Since 2008, bitcoin has continued to attract investors due to its growing capitalization and opportunity for speculation. The purpose of this paper is to analyze the impact of…
Abstract
Purpose
Since 2008, bitcoin has continued to attract investors due to its growing capitalization and opportunity for speculation. The purpose of this paper is to analyze the impact of bitcoin (BTC) on gold, the volatility index (VIX) and the dollar index (USDX).
Design/methodology/approach
The series used are weekly and cover the period from January 2016 to November 2022. To generate the results, the unrestricted vector autoregression (VAR), structural vector autoregression (SVAR) and wavelet coherence were performed.
Findings
The findings are mixed as not all tests show the exact effects of BTC in the three asset classes. However, common to all the tests is the significant influence that BTC maintains on gold and vice versa. The positive shock in BTC significantly increases the gold prices, confirmed in three different tests. The effects on the VIX and USDX are still being determined, where in some tests, it appears to be influential while in others not.
Originality/value
BTC’s diversification potential with equity stocks and USDX makes it a valuable security for portfolio managers. Furthermore, regulatory authorities should consider that BTC is not an isolated phenomenon and can significantly influence other asset classes such as gold.
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Shinta Amalina Hazrati Havidz, Esperanza Vera Anastasia, Natalia Shirley Patricia and Putri Diana
We investigated the association of COVID-19 indicators and economic uncertainty indices on payment-based system cryptocurrency (i.e. Bitcoin, Ripple and Dogecoin) returns.
Abstract
Purpose
We investigated the association of COVID-19 indicators and economic uncertainty indices on payment-based system cryptocurrency (i.e. Bitcoin, Ripple and Dogecoin) returns.
Design/methodology/approach
We used an autoregressive distributed lag (ARDL) model for panel data and performed robustness checks by utilizing a random effect model (REM) and generalized method of moments (GMM). There are 25 most adopted cryptocurrency’s countries and the data spans from 22 March 2021 to 6 May 2022.
Findings
This research discovered four findings: (1) the index of COVID-19 vaccine confidence (VCI) recovers the economic and Bitcoin has become more attractive, causing investors to shift their investment from Dogecoin to Bitcoin. However, the VCI was revealed to be insignificant to Ripple; (2) during uncertain times, Bitcoin could perform as a diversifier, while Ripple could behave as a diversifier, safe haven or hedge. Meanwhile, the movement of Dogecoin prices tended to be influenced by public figures’ actions; (3) public opinion on Twitter and government policy changes regarding COVID-19 and economy had a crucial role in investment decision making; and (4) the COVID-19 variants revealed insignificant results to payment-based system cryptocurrency returns.
Originality/value
This study contributed to verifying the vaccine confidence index effect on payment-based system cryptocurrency returns. Also, we further investigated the uncertainty indicators impacting on cryptocurrency returns during the COVID-19 pandemic. Lastly, we utilized the COVID-19 variants as a cryptocurrency returns’ new determinant.
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This study aims to examine the cryptocurrency adoption (CA) level among Indian retail investors who use cryptocurrency as an investment and mode of transaction.
Abstract
Purpose
This study aims to examine the cryptocurrency adoption (CA) level among Indian retail investors who use cryptocurrency as an investment and mode of transaction.
Design/methodology/approach
Through self-administered survey questionnaires, data is collected from 397 retail investors of Haryana (India). This study adopted a quantitative method using partial least squares structural equation modeling (PLS-SEM).
Findings
This paper offered a robust model with a high explanatory value for CA in which four of the five proposed factors of diffusion of innovation theory (trialability, compatibility, complexity and observability) and one of the two proposed factors of consumer behavioral theory (perceived value) significantly influences CA. More specifically, the absence of regulatory support is a barrier to the broad adoption of cryptocurrencies, as its regulations are necessary to mitigate or minimize uncertain outcomes.
Research limitations/implications
This research primarily focuses on CA in India. Thus, it can be extended to cover diverse other countries for more precise results.
Practical implications
The results provide insights to the government to design the policies, better regulate and make investment strategies that can ultimately enhance CA. In addition, the study’s results also inform financial educators, policymakers, employers and academicians about the significance of several variables affecting CA in India.
Social implications
From a social standpoint, this study is an advance that directs central banks and governments to develop, regulate and manage digital currencies and implement a digital currency ecosystem. Moreover, the results assist in understanding investors’ perceptions and decision-making perspectives toward cryptocurrencies through the country’s digitalization.
Originality/value
This paper fills the study gap to assist policymakers and cryptocurrency experts in broadening their knowledge base and recognizing prioritized intentions. Additionally, this study provides a theoretical model with the latent variable for a present and pertinent matter.
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Yadong Liu, Nathee Naktnasukanjn, Anukul Tamprasirt and Tanarat Rattanadamrongaksorn
Bitcoin (BTC) is significantly correlated with global financial assets such as crude oil, gold and the US dollar. BTC and global financial assets have become more closely related…
Abstract
Purpose
Bitcoin (BTC) is significantly correlated with global financial assets such as crude oil, gold and the US dollar. BTC and global financial assets have become more closely related, particularly since the outbreak of the COVID-19 pandemic. The purpose of this paper is to formulate BTC investment decisions with the aid of global financial assets.
Design/methodology/approach
This study suggests a more accurate prediction model for BTC trading by combining the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model with the artificial neural network (ANN). The DCC-GARCH model offers significant input information, including dynamic correlation and volatility, to the ANN. To analyze the data effectively, the study divides it into two periods: before and during the COVID-19 outbreak. Each period is then further divided into a training set and a prediction set.
Findings
The empirical results show that BTC and gold have the highest positive correlation compared with crude oil and the USD, while BTC and the USD have a dynamic and negative correlation. More importantly, the ANN-DCC-GARCH model had a cumulative return of 318% before the outbreak of the COVID-19 pandemic and can decrease loss by 50% during the COVID-19 pandemic. Moreover, the risk-averse can turn a loss into a profit of about 20% in 2022.
Originality/value
The empirical analysis provides technical support and decision-making reference for investors and financial institutions to make investment decisions on BTC.
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