A0194
Title: Robust estimation of the range-based GARCH model: Application for cryptocurrencies
Authors: Piotr Fiszeder - Nicolaus Copernicus University in Torun (Poland) [presenting]
Marta Malecka - University of Lodz (Poland)
Abstract: The range-based GARCH model is combined with the modified robust estimation method and suggests a new approach to model the volatility of returns. Thanks to this merger, more information is used, commonly available alongside daily closing prices, i.e., low and high prices. However, the influence of extreme observations is limited in the estimation results. Owing to this, the procedure is not as sensitive to outliers as the maximum likelihood estimation of the range-based models. Introduce the change to the robust method is also proposed, which adds elasticity in treating the outliers and serves to reflect the observations of financial markets, where, after the occurrence of outliers, the volatility persists at an increased level. This method is applied to five selected cryptocurrencies: Bitcoin, Ethereum Classic, Ethereum, Litecoin and Ripple. The forecasts of variance based on the proposed approach are more accurate than forecasts from three benchmarks: the standard GARCH model, the standard range-based GARCH model and the GARCH model with the robust estimation.
