Risks in Major Cryptocurrency Markets: Modeling the Dual Long Memory Property and Structural Breaks

This study estimates the effects of dual long memory property and structural breaks on persistence level six major cryptocurrency markets. We apply Bai Perron break test, Inclán Tiao’s iterated cumulative sum squares (ICSS) algorithm, fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model, with different distributions. The results show that characterize volatility markets, confirming our hypothesis ignoring leads to an underestimation modeling. ARFIMA-FIGARCH a skewed Student-t distribution, fits market’s price dynamics well.