 The adaptive market hypothesis in the high frequency cryptocurrency marketJeffrey Chu, Yuanyuan Zhang and Stephen Chan International Review of Financial Analysis, 2019, vol. 64, issue C, 221-231 Abstract: This paper investigates the adaptive market hypothesis (AMH) with respect to the high frequency markets of the two largest cryptocurrencies — Bitcoin and Ethereum, versus the Euro and US Dollar. Our findings are consistent with the AMH and show that the efficiency of the markets varies over time. We also discuss possible news and events which coincide with significant changes in the market efficiency. Furthermore, we analyse the effect of the sentiment of these news and other factors (events) on the market efficiency in the high frequency setting, and provide a simple event analysis to investigate whether specific factors affect the market efficiency/inefficiency. The results show that the sentiment and types of news and events may not be significant factor in determining the efficiency of cryptocurrency markets. Keywords: Bitcoin; Ethereum; Martingale difference hypothesis; Adaptive market hypothesis; Efficient market hypothesis (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:eee:finana:v:64:y:2019:i:c:p:221-231 DOI: 10.1016/j.irfa.2019.05.008 Access Statistics for this article International Review of Financial Analysis is currently edited by B.M. Lucey More articles in International Review of Financial Analysis from Elsevier |
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