The adaptive market hypothesis in the high frequency cryptocurrency market

Jeffrey Chu*, Yuanyuan Zhang, Stephen Chan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)221-231
Number of pages11
JournalInternational Review of Financial Analysis
Volume64
Early online date6 Jun 2019
DOIs
Publication statusPublished - Jul 2019

Keywords

  • Adaptive market hypothesis
  • Bitcoin
  • Efficient market hypothesis
  • Ethereum
  • Martingale difference hypothesis

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