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Discovering interlinkages between major cryptocurrencies using high‑frequency data : new evidence from COVID‑19 pandemic
Yousaf, Imran; Ali, Shoaib - In: Financial innovation : FIN 6 (2020) 45, pp. 1-18
Through the application of the VAR-AGARCH model to intra-day data for three cryp-tocurrencies (Bitcoin, Ethereum, and … period and the COVID-19 period. We also estimate the optimal weights, hedge ratios, and hedging effectiveness during both … sample periods. We find that the return spillovers vary across the two periods for the Bitcoin-Ethereum, Bitcoin …
Persistent link: https://www.econbiz.de/10012317582
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A new proof-of-work mechanism for bitcoin
Shi, Ning - In: Financial innovation : FIN 2 (2016) 31, pp. 1-8
Background: Bitcoin system, when more than 51% computing power is controlled by a single node, the block chain can be … distorted maliciously. This is called 51% attack which is a well-known potential risk that could destroy the Bitcoin system …
Persistent link: https://www.econbiz.de/10011590629
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Unsupervised clustering of bitcoin transactions
Vlahavas, George; Karasavvas, Kostas; Vakali, Athena - In: Financial innovation : FIN 10 (2024), pp. 1-31
Since its inception in 2009, Bitcoin has become and is currently the most successful and widely used cryptocurrency. It … publicly available and auditable, making Bitcoin a pseudoanonymous ledger of transactions. The volume of transactions that are …
Persistent link: https://www.econbiz.de/10014532062
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Understanding the adoption context of China's digital currency electronic payment
Xia, Huosong; Gao, Yangmei; Zhang, Zuopeng - In: Financial innovation : FIN 9 (2023) 1, pp. 1-27
Central banks worldwide have started researching and developing central bank digital currencies (CBDCs). In the digital economy context, concerns regarding the integrity, competition, and privacy of CBDC systems have also gradually emerged. Against this backdrop, this study aims to evaluate...
Persistent link: https://www.econbiz.de/10014289053
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Time-varying spillovers in high-order moments among cryptocurrencies
Azimli, Asil - In: Financial innovation : FIN 10 (2024), pp. 1-39
.e. Bitcoin, Ethereum, Binance, Cardano, Litecoin, and Ripple) at volatility and high-order (third and fourth orders in this paper … kurtosis connectedness networks were dominated by Litecoin and Bitcoin and Ripple were net shock receivers in all three …
Persistent link: https://www.econbiz.de/10014540286
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Asymmetric connectedness between conventional and Islamic cryptocurrencies : evidence from good and bad volatility spillovers
Bouri, Elie; Asl, Mahdi Ghaemi; Darehshiri, Sahar; … - In: Financial innovation : FIN 10 (2024), pp. 1-26
nearly 61% of cryptocurrency market capitalization and covering both conventional (Bitcoin and Ethereum) and Islamic (Stellar …
Persistent link: https://www.econbiz.de/10014548184
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Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets
Mensi, Walid; Gubareva, Mariya; Ko, Hee-Un; Xuan Vinh Vo; … - In: Financial innovation : FIN 9 (2023) 1, pp. 1-27
This study investigates tail dependence among five major cryptocurrencies, namely Bitcoin, Ethereum, Litecoin, Ripple …, and Bitcoin Cash, and uncertainties in the gold, oil, and equity markets. Using the cross-quantilogram method and quantile …
Persistent link: https://www.econbiz.de/10014289114
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Heterogeneity in the volatility spillover of cryptocurrencies and exchanges
Wu, Meiyu; Wang, Li; Yang, Haijun - In: Financial innovation : FIN 10 (2024), pp. 1-46
This study examines the volatility spillovers in four representative exchanges and for six liquid cryptocurrencies. Using the high-frequency trading data of exchanges, the heterogeneity of exchanges in terms of volatility spillover can be examined dynamically in the time and frequency domains....
Persistent link: https://www.econbiz.de/10014547084
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The witching week of herding on bitcoin exchanges
Blasco de las Heras, Natividad; Corredor, Pilar; … - In: Financial innovation : FIN 8 (2022), pp. 1-18
This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the … exchanges that trade bitcoin (Binance, Bitfinex, Bitstamp, Coinbase, itBit, Kraken, and Gemini) and using hourly closing prices … and trading volumes in bitcoin and US dollars. Adapting the proposal of Chang, Cheng and Khorana (2000) (CCK) to test …
Persistent link: https://www.econbiz.de/10013169971
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On the factors of Bitcoin's value at risk
Kwon, Ji Ho - In: Financial innovation : FIN 7 (2021), pp. 1-31
This study investigates the factors of Bitcoin's tail risk, quantified by Value at Risk (VaR). Extending the … conditional autoregressive VaR model proposed by Engle and Manganelli (2004), I examine 30 potential drivers of Bitcoin's 5% and 1 …% VaR. For the 5% VaR, quantity variables, such as Bitcoin trading volume and monetary policy rate, were positively …
Persistent link: https://www.econbiz.de/10012798684