Cyber-attacks, spillovers and contagion in the cryptocurrency markets

Caporale, Guglielmo Maria; Kang, Woo−Young; Spagnolo, Fabio; Spagnolo, Nicola

doi:10.1016/j.intfin.2021.101298

Cited by 62 publications

(15 citation statements)

References 65 publications

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“…The likelihood of arbitrage opportunities is highly related to the information flow among crypto-currency exchanges, more specifically, cross-market mean and volatility spillovers. Understanding the connections between different markets is fundamental for portfolio diversification, hedging, risk management, and arbitrage purposes [23]. Moreover, the transmission of spillovers between markets is generally seen as a result of increased integration, and also because of the presence of financial contagion or systemic risk [24,25].…”

Section: Related Workmentioning

confidence: 99%

Key Roles of Crypto-Exchanges in Generating Arbitrage Opportunities

Kabašinskas

Šutienė

2021

Entropy

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The evolving crypto-currency market is seen as dynamic, segmented, and inefficient, coupled with a lack of regulatory oversight, which together becomes conducive to observing the arbitrage. In this context, a crypto-network is designed using bid/ask data among 20 crypto-exchanges over a 2-year period. The graph theory technique is employed to describe the network and, more importantly, to determine the key roles of crypto-exchanges in generating arbitrage opportunities by estimating relevant network centrality measures. Based on the proposed arbitrage ratio, Gatecoin, Coinfloor, and Bitsane are estimated as the best exchanges to initiate arbitrage, while EXMO and DSX are the best places to close it. Furthermore, by means of canonical correlation analysis, we revealed that higher volatility and the decreasing price of dominating crypto-currencies and CRIX index signal bring about a more likely arbitrage appearance in the market. The findings of research include pre-tax and after-tax arbitrage opportunities.

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Section: Related Workmentioning

confidence: 99%

Key Roles of Crypto-Exchanges in Generating Arbitrage Opportunities

Kabašinskas

Šutienė

2021

Entropy

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“…Contrary to the existing literature, we base our analysis on ultrahigh-frequency data, using second-by-second observations to compute realised volatility at the fiveminute frequency which, due to microstructure noise, is the highest frequency which allows a reliable transmission analysis. All other studies on volatility spillovers between different cryptocurrencies (Yi et al, 2018;Katsiampa et al, 2019;Wang and Ngene, 2020;Caporale et al, 2021;Sensoy et al, 2021) or between individual crypto-exchanges (Ji et al, 2021) rely on daily observations, and/or they focus exclusively on the much smaller spot market, which could lead to erroneous conclusions. By analysing realised volatility on major spot and derivatives exchanges at the 5-minute frequency we study more afterwards a U.S. senator Don Beyer presented congress with a 58-page draft of the Digital Asset Market Structure and Investor Protection Act, proposing sweeping reforms and clarifying the responsibilities of the Federal Reserve, the SEC and the CFTC.…”

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confidence: 99%

The Role of Binance in Bitcoin Volatility Transmission

Alexander¹,

Heck²,

Kaeck³

2021

Preprint

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We analyse high-frequency realised volatility dynamics and spillovers between centralised crypto exchanges that offer spot and derivatives contracts for bitcoin against the U.S. dollar or the stable coin tether. The tether-margined perpetual contract on Binance is clearly the main source of volatility, continuously transmitting strong flows to all other instruments and receiving very little volatility from other sources. We also find that crypto exchanges exhibit much higher interconnectedness when traditional Western stock markets are open. Especially during the U.S. time zone, volatility outflows from Binance are much higher than at other times, and Bitcoin traders are more attentive and reactive to prevailing market conditions. Our results highlight that market regulators should pay more attention to the tether-margined derivatives products available on most self-regulated exchanges, most importantly on Binance.

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“…Positive returns may lead to changes in investor expectations 17 Bouri et al ( 2021b ) Diebold and Yilmaz ( 2012 ) based on quantile VAR 8 August 2015 to 31 December 2020 Bitcoin, Ethereum, Litecoin, Dash, Monero, Ripple, and Stellar Connectedness becomes stronger with the magnitude of positive and negative shocks. Return connectedness over extreme market conditions is asymmetric 18 Luu Duc Huynh ( 2019 ) SVAR; Granger causality; Student’s-t Copulas 8 September 2015 to 4 January 2019 Bitcoin, Litecoin, Ethereum, Xrp, and Stellar Ethereum is disentangled from the spillover network, whereas Bitcoin is the spillover recipient 19 Caporale et al ( 2021 ) Trivariate GARCH-BEKK 12 August 2015 to 15 January 2020 Bitcoin, Ethereum, and Litecoin Cyber-attacks influence the spillover transmission between cryptocurrency return and volatility, strengthening the connection and thus reducing opportunities for portfolio diversification 20 Huynh et al ( 2020 ) Transfer Entropy April 2013 to April 2019 14 Cryptocurrencies Cryptocurrencies with smaller market capitalization turn out to be shock transmitters than the larger ones VAR, Vector Auto-Regression; GARCH, Generalized Autoregressive Conditional Heteroskedasticity; MGARCH, Multivariate Generalized Autoregressive Conditional Heteroskedasticity; DCC, Dynamic Conditional Correlation; SVAR, Structural Vector Auto-Regression; TVP-FAVAR, Time-Varying Parameter Factor Augmented VAR; BEKK, Baba, Engle, Kraft, and Kroner; GJR, Glosten-Jagannathan-Runkle; TENET, Tail-Event driven NETwork; GSADF, Generalized Supremum Augmented Dickey-Fuller; LASSO, Least Absolute Selection and Shrinkage Operator …”

Section: Literature Reviewmentioning

confidence: 99%

Liquidity connectedness in cryptocurrency market

et al. 2022

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We examine the dynamics of liquidity connectedness in the cryptocurrency market. We use the 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) on a sample of six major cryptocurrencies, namely, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Monero (XMR), and Dash. Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies, whereas BTC and LTC play a significant role in connectedness magnitude. A distinct liquidity cluster is observed for BTC, LTC, and XRP, and ETH, XMR, and Dash also form another distinct liquidity cluster. The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium- and long-run time horizons. In the short run, BTC, LTC, and XRP are the leading contributor to liquidity shocks, whereas, in the long run, ETH assumes this role. Compared with the medium term, a tight liquidity clustering is found in the short and long terms. The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time, pointing to the possible effect of rising demand and higher acceptability for this unique asset. Furthermore, more pronounced liquidity connectedness patterns are observed over the short and long run, reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time–frequency connectedness.

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Cyber-attacks, spillovers and contagion in the cryptocurrency markets

Cited by 62 publications

References 65 publications

Key Roles of Crypto-Exchanges in Generating Arbitrage Opportunities

Key Roles of Crypto-Exchanges in Generating Arbitrage Opportunities

The Role of Binance in Bitcoin Volatility Transmission

Liquidity connectedness in cryptocurrency market

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