2016
DOI: 10.2139/ssrn.2733736
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Do Co-Jumps Impact Correlations in Currency Markets?

Abstract: We quantify how co-jumps impact correlations in currency markets. To disentangle the continuous part of quadratic covariation from co-jumps, and study the influence of co-jumps on correlations, we propose a new wavelet-based estimator. The proposed estimation framework is able to localize the co-jumps very precisely through wavelet coefficients and identify statistically significant co-jumps. Empirical findings reveal the different behaviors of co-jumps during Asian, European and U.S. trading sessions. Importa… Show more

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Cited by 2 publications
(2 citation statements)
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References 85 publications
(58 reference statements)
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“…Moreover, currencies with greater liquidity (measured by trading volume) tend to more quickly recover their price stability. Using a novel jump wavelet covariance estimator, Barunik and Vacha (2018) quantify the impact of co‐jumps on currency markets' correlations. The authors identify a variety of impact behaviour from co‐jumps on the currencies modelled during the Asian, European, and U.S. trading sessions.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Moreover, currencies with greater liquidity (measured by trading volume) tend to more quickly recover their price stability. Using a novel jump wavelet covariance estimator, Barunik and Vacha (2018) quantify the impact of co‐jumps on currency markets' correlations. The authors identify a variety of impact behaviour from co‐jumps on the currencies modelled during the Asian, European, and U.S. trading sessions.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Moreover, the use of a maximum overlap discrete wavelet transformation rather than a discrete wavelet transformation, as in [12], enabled them to provide an exact point estimate of the jump location. Moreover, Barunik and Vacha [14] implemented wavelet-based jump localization techniques in multivariate asset price processes showing that wavelets are very useful in detection and localization of the co-jumps in the multivariate data.…”
Section: Introductionmentioning
confidence: 99%