Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Time-Transformed Test for Bubbles under Non-stationary Volatility. / Kurozumi, Eiji; Скроботов, Антон Андреевич; Tsarev, Alexey.
в: Journal of Financial Econometrics, 23.04.2022.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Time-Transformed Test for Bubbles under Non-stationary Volatility
AU - Kurozumi, Eiji
AU - Скроботов, Антон Андреевич
AU - Tsarev, Alexey
PY - 2022/4/23
Y1 - 2022/4/23
N2 - This paper is devoted to testing for bubbles under time-varying non-stationary volatility. Because the limiting distribution of the seminal Phillips, Wu, and Yu (2011) test depends on the variance function and usually requires a bootstrap implementation under heteroskedasticity, we construct the test based on a deformation of the time domain. The proposed test is asymptotically pivotal under the null hypothesis and its limiting distribution coincides with that of the standard test under homoskedasticity, so that the test does not require computationally extensive methods for inference. Appealing finite sample properties are demonstrated through Monte-Carlo simulations. An empirical application demonstrates that the upsurge behavior of cryptocurrency time series in the middle of the sample is partially explained by the volatility change.
AB - This paper is devoted to testing for bubbles under time-varying non-stationary volatility. Because the limiting distribution of the seminal Phillips, Wu, and Yu (2011) test depends on the variance function and usually requires a bootstrap implementation under heteroskedasticity, we construct the test based on a deformation of the time domain. The proposed test is asymptotically pivotal under the null hypothesis and its limiting distribution coincides with that of the standard test under homoskedasticity, so that the test does not require computationally extensive methods for inference. Appealing finite sample properties are demonstrated through Monte-Carlo simulations. An empirical application demonstrates that the upsurge behavior of cryptocurrency time series in the middle of the sample is partially explained by the volatility change.
UR - https://www.mendeley.com/catalogue/4652ba8e-fabe-3716-9c61-d9de9c2e2624/
U2 - 10.1093/jjfinec/nbac004
DO - 10.1093/jjfinec/nbac004
M3 - Article
JO - Journal of Financial Econometrics
JF - Journal of Financial Econometrics
SN - 1479-8409
ER -
ID: 94525918