Adaptive long memory in volatility of intra-day bitcoin returns and the impact of trading volume

Sashikanta Khuntia and J.K. Pattanayak

Finance Research Letters, 2020, vol. 32, issue C

Abstract: This paper evaluates the adaptive pattern of long memory in the volatility of intra-day bitcoin returns. It also tests the impact of the trading volume on time-varying long memory. Our finding confirms long memory in the volatility of intra-day bitcoin returns is not an all-or-nothing phenomenon; it is adaptive to change in time and creation of events and, therefore, adheres to the proposition of the adaptive market hypothesis. This paper reveals the explanatory power of trading volume on long memory during bearish and bullish movements.

Keywords: Bitcoin; Cryptocurrencies; Volatility; Long memory; Adaptive market hypothesis (search for similar items in EconPapers)
JEL-codes: G12 G14 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:32:y:2020:i:c:s1544612318305488

DOI: 10.1016/j.frl.2018.12.025

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