On fitting cryptocurrency log-return exchange rates

Ayman Alzaatreh, Hana Sulieman

Research output: Contribution to journalArticlepeer-review

Abstract

Cryptocurrency has become the leading method for peer-to-peer electronic cash system. It uses cryptography to secure financial transactions. Recently, several researchers have attempted to understand the behaviors of cryptocurrency exchange rates. In this paper, we introduce a new location–scale family of distributions to understand the distributional properties of the log-return exchange rates of cryptocurrencies. We use quantile kurtosis measures to show that the proposed family of distributions provides a desirable level of flexibility in terms of skewness and tail heaviness. Several recent data on US dollar-based cryptocurrency exchange rates have been analyzed, and the results are compared against those of the generalized hypergeometric distribution. It is shown that the proposed family of distributions possesses desired features including model simplicity, shape flexibility and quality of distribution fit.

Original languageEnglish
JournalEmpirical Economics
DOIs
Publication statusAccepted/In press - Jan 1 2019

Keywords

  • Cryptocurrency
  • Distribution
  • Kurtosis
  • Quantile
  • T- X family

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics (miscellaneous)
  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Fingerprint Dive into the research topics of 'On fitting cryptocurrency log-return exchange rates'. Together they form a unique fingerprint.

Cite this