Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19

Assaf, Ata; Bhandari, Avishek; Charif, Husni; Demir, Ender

doi:10.1016/j.irfa.2022.102132

Cited by 33 publications

(13 citation statements)

References 93 publications

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“…Specifically, cryptocurrencies tend to form bigger groups during the downtime, i.e., the number of potential clusters found in the network decreases during the downtime, with a few cryptocurrencies acting as central nodes. This topic has only been explored in a few studies to date [ 21 , 22 , 45 , 46 ]. Moreover, there are some gaps: (1) the lack of deep investigation of the network structure as they only consider MSTs; (2) the noise and trend effects are not removed; (3) data limitation issues.…”

Section: Related Workmentioning

confidence: 99%

The Cryptocurrency Market in Transition before and after COVID-19: An Opportunity for Investors?

Nguyen

Tan

Bezbradica

et al. 2022

Entropy

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We analyze the correlation between different assets in the cryptocurrency market throughout different phases, specifically bearish and bullish periods. Taking advantage of a fine-grained dataset comprising 34 historical cryptocurrency price time series collected tick-by-tick on the HitBTC exchange, we observe the changes in interactions among these cryptocurrencies from two aspects: time and level of granularity. Moreover, the investment decisions of investors during turbulent times caused by the COVID-19 pandemic are assessed by looking at the cryptocurrency community structure using various community detection algorithms. We found that finer-grain time series describes clearer the correlations between cryptocurrencies. Notably, a noise and trend removal scheme is applied to the original correlations thanks to the theory of random matrices and the concept of Market Component, which has never been considered in existing studies in quantitative finance. To this end, we recognized that investment decisions of cryptocurrency traders vary between bearish and bullish markets. The results of our work can help scholars, especially investors, better understand the operation of the cryptocurrency market, thereby building up an appropriate investment strategy suitable to the prevailing certain economic situation.

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Section: Related Workmentioning

confidence: 99%

The Cryptocurrency Market in Transition before and after COVID-19: An Opportunity for Investors?

Nguyen

Tan

Bezbradica

et al. 2022

Entropy

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“…Cryptocurrencies are renowned for their extreme volatility and long-term fluctuations brought on by investors’ emotions; they are not traded on regulated markets and are not subject to the same regulations as traditional financial instruments (Assaf et al 2022 ). Sentiment analysis is a widely researched field in the era of social media and has been employed to boost trading cryptocurrency estimations (Fang et al 2022 ).…”

Section: Prior Literaturementioning

confidence: 99%

Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

Gherghina

Simionescu

2023

Financ Innov

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This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the coronavirus indices (Panic, Hype, Fake News, Sentiment, Infodemic, and Media Coverage), on the cryptocurrency market. Using daily data from January 2020 to September 2021 and the exponential generalized autoregressive conditional heteroskedasticity model, the results revealed that both adverse and optimistic news had the same effect on Bitcoin returns, indicating fear of missing out behavior does not prevail. Furthermore, when the nonlinear autoregressive distributed lag model is estimated, both positive and negative shocks in pandemic indices promote Bitcoin’s daily changes; thus, Bitcoin is resistant to the SARS-CoV-2 pandemic crisis and may serve as a hedge during market turmoil. The analysis of frequency domain causality supports a unidirectional causality running from the Coronavirus Fake News Index and Sentiment Index to Bitcoin returns, whereas daily fluctuations in the Bitcoin price Granger affect the Coronavirus Panic Index and the Hype Index. These findings may have significant policy implications for investors and governments because they highlight the importance of news during turbulent times. The empirical results indicate that pandemic news could significantly influence Bitcoin’s price.

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“…Several papers have employed different techniques to rank market efficiency in a variety of markets ( [5], [8], [9], [39], [37], [36], [22], [33], [30], and [43]). In line with these papers, our results suggest that the cryptocurrency market is constantly evolving and exogenous shocks cause changes in the dynamics of these prices.…”

Section: Introductionmentioning

confidence: 99%

Assessment the predictability in the price dynamics for top ten cryptocurrencies: The impacts of Russia-Ukraine war

Araujo

Fernandes

Silva

et al. 2023

Preprint

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This paper has investigated the predictability of the top ten cryptocurrencies’ price dynamics, ranked by their daily market capitalization and trade volume, via the information theory quantifiers. Our analysis considers the Complexity-entropy causality plane to study the temporal evolution of the price of these cryptocurrencies and their respective locations along this 2D map, bearing in mind after and during the Russia-Ukraine war. Moreover, we apply the permutation entropy and the Jensen-Shannon statistical complexity measure to rank these cryptocurrencies similarly to a complexity hierarchy. Our findings reflect that the Russian-Ukraine war affects the informational efficiency of cryptocurrency dynamics. Specifically, the cryptocurrencies notably showed a decrease in informational inefficiency (USD-coin, Binance-USD, BNB, Dogecoin, and XRP). At the same time, the cryptocurrencies with more expressiveness for the financial market, considering the volume traded and the capitalized market, were strongly impacted, presenting an increase in informational inefficiency (Tether, Cardano, Ethereum, and Bitcoin). It clarifies the potential of cryptocurrencies to mitigate exogenous shocks and their capability to use with portfolio selection, risk diversification and herding behaviour.

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Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19

Cited by 33 publications

References 93 publications

The Cryptocurrency Market in Transition before and after COVID-19: An Opportunity for Investors?

The Cryptocurrency Market in Transition before and after COVID-19: An Opportunity for Investors?

Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

Assessment the predictability in the price dynamics for top ten cryptocurrencies: The impacts of Russia-Ukraine war

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