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Comparative Analysis of the Volatility Structure of Cryptocurrencies

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  • Fatih Kazova

    (Akdeniz Universitesi, Iktisadi ve Idari Bilimler Fakultesi, Ekonometri Bolumu, Antalya, Turkiye)

  • Ayça Büyükyılmaz Ercan

    (Akdeniz Universitesi, Iktisadi ve Idari Bilimler Fakultesi, Ekonometri Bolumu, Antalya, Turkiye)

Abstract

Cryptocurrency emerged as an alternative medium of exchange developed after the 2008 global financial crisis to replace the traditional money system. Cryptocurrencies have become increasingly popular because of their fast and secure transactions, elimination of intermediaries, and low cost. However, due to the high risk–return ratio arising from sharp fluctuations in the cryptomoney market, studies have emphasized that the risks of cryptocurrencies should be considered in addition to their returns. This study investigates the effects of positive and negative shocks on the volatility of the rates of return on cryptocurrencies. In this direction, a return series was created by choosing BTC, ETH, XRP, ADA, LTC, BCH, XLM, LINK, TRX, and DOGE cryptocurrencies with high market values. The volatility of these return series was analyzed using symmetric and asymmetric conditional heteroskedasticity models. Although the data set period varies for each cryptocurrency, the largest dataset covers the period from January 1, 2017, to January 16, 2021. The findings show that negative shocks in BTC, ADA, and LINK return series have more effect on volatility than positive shocks. Alternatively, it was concluded that positive shocks have a greater effect on volatility in ETH, XRP, LTC, BCH, XLM, TRX, DOGE return series. Therefore, for the data used in this study, it has been shown that the asymmetric conditional heteroskedasticity models give more meaningful results than the symmetric conditional heteroskedasticity models in modeling the volatility of the return series.

Suggested Citation

  • Fatih Kazova & Ayça Büyükyılmaz Ercan, 2021. "Comparative Analysis of the Volatility Structure of Cryptocurrencies," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(35), pages 33-57, December.
    • Handle: RePEc:ist:ekoist:v:0:y:2021:i:35:p:33-57
    DOI: 10.26650/ekoist.2021.36.984568
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