 Time-Transformed Test for Bubbles under Non-stationary Volatility*Eiji Kurozumi, Anton Skrobotov and Alexey Tsarev Journal of Financial Econometrics, 2023, vol. 21, issue 4, 1282-1307 Abstract: 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. Keywords: explosive autoregression; rational bubble; right-tailed unit root testing; time-transformed data; time-varying volatility; variance profile (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:jfinec:v:21:y:2023:i:4:p:1282-1307. Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani More articles in Journal of Financial Econometrics from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC. |
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