2023
DOI: 10.2139/ssrn.4390758
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Trading Stranded Assets on the Ftx Exchange

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Cited by 1 publication
(9 citation statements)
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“…We employ a methodology similar to that used by De Blasis et al ( 2023) and Galati et al (2023), who use a BEKK-GARCH model to find evidence of contagion effects between stablecoins during the Terra token crash (De Blasis et al, 2023) and cryptocurrencies during the FTX collapse (Galati et al, 2023), to test for financial contagion across digital assets. Developed by Engle and Kroner (1995), the BEKK model belongs to the family of multivariate GARCH models used to assess conditional covariances and correlations, thus the interaction between time series, and is preferred over the similar DCC-GARCH model (Caporin & McAleer, 2012).…”
Section: Methodsmentioning
confidence: 99%
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“…We employ a methodology similar to that used by De Blasis et al ( 2023) and Galati et al (2023), who use a BEKK-GARCH model to find evidence of contagion effects between stablecoins during the Terra token crash (De Blasis et al, 2023) and cryptocurrencies during the FTX collapse (Galati et al, 2023), to test for financial contagion across digital assets. Developed by Engle and Kroner (1995), the BEKK model belongs to the family of multivariate GARCH models used to assess conditional covariances and correlations, thus the interaction between time series, and is preferred over the similar DCC-GARCH model (Caporin & McAleer, 2012).…”
Section: Methodsmentioning
confidence: 99%
“…Developed by Engle and Kroner (1995), the BEKK model belongs to the family of multivariate GARCH models used to assess conditional covariances and correlations, thus the interaction between time series, and is preferred over the similar DCC-GARCH model (Caporin & McAleer, 2012). Consistent with De Blasis et al ( 2023) and Galati et al (2023), we assume that the logarithmic returns follow a normal distribution with zero means and the variance-covariance matrix 𝐻 𝑑 , so that we can model the conditional covariances as…”
Section: Methodsmentioning
confidence: 99%
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