Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?
نویسندگان
چکیده
This study proposes a new approach for testing random walk behavior in daily Bitcoin returns (19/07/2010–03/03/2022) by contextualizing the Dickey-Fuller test time-frequency space using continuous complex wavelet transforms. By splitting our full sample into smaller sub-sample periods segregated halving dates, we find that are most predictable or least market efficient (i) at higher frequency short-run cycles of between 2 and 16 days, (ii) November-February months, (iii) during ‘bubble’ periods, (iv) across consecutive (v) ‘Black Swan event’ caused financial turmoil arising from COVID-19 pandemic, (vi) subsequent to announcements variants. Altogether, findings have important policy implications different stakeholders markets.
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ژورنال
عنوان ژورنال: Eurasian Economic Review
سال: 2022
ISSN: ['1309-422X']
DOI: https://doi.org/10.1007/s40822-022-00214-8