Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum

By Walid Mensi, K. Al-Yahyaee, Sang Hoon Kang. Finance Research Letters, 2019

138 citations recorded by the source corpus.

This study explores the impacts of structural breaks (SB) on the dual long memory levels of Bitcoin and Ethereum price returns. We identify dual long memory and structural changes on cryptocurrency markets using four different generalized autoregressive conditional heteroskedasticity models (e.g., GARCH, FIGARCH, FIAPARCH, and HYGARCH). Furthermore, the persistence level of both returns and volatility decreases after accounting for long memory and switching states. Finally, the FIGARCH model with SB variables provides a comparatively superior forecasting accuracy performance. These findings have significant implications for both cryptocurrency allocations and portfolio management.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/60e40da4b65797e97f1153852c60b86eba62feb4

Citations in the corpus

• An empirical investigation of volatility dynamics in the cryptocurrency market (2019, unknown): “In addition, the extreme value behaviour of cryptocurrencies has been studied by Osterrieder and Lorenz (2017), Osterrieder et al. (2017), and Gkillas and Katsiampa (2018), all of whom have shown that cryptocurrencies exhibit heavier tail behaviour and are thus riskier than fiat currencies.”