Stylised facts for high frequency cryptocurrency data Articles uri icon

authors

  • Zhang, Yuanyuan
  • Nadarajah, Saralees
  • Chan, Stephen
  • CHU, JEFFREY

publication date

  • January 2018

start page

  • 598

end page

  • 612

volume

  • 513

International Standard Serial Number (ISSN)

  • 0378-4371

Electronic International Standard Serial Number (EISSN)

  • 1873-2119

abstract

  • The term 'stylised facts' has been extensively researched through the analysis of many different financial datasets. More recently, cryptocurrencies have been investigated as a new type of financial asset, and provide an interesting example, with a current market value of over $500 billion. Here, we analyse the stylised facts in terms of the Hurst exponent, using both the DFA and RCS methods, of the four most popular cryptocurrencies ranked according to their market capitalisation. The analysis is conducted on high frequency returns data with varying lags. In addition to using the Hurst exponent, our analysis also considers features of dependence between the different cryptocurrencies. (C) 2018 Elsevier B.V. All rights reserved.

keywords

  • bitcoin; ethereum; hurst exponent; tail dependence