Volatility estimation using a rational GARCH model

Abstract

The rational GARCH (RGARCH) model has been proposed as an alternative GARCHmodel that captures the asymmetric property of volatility. In addition to the previously proposedRGARCH model, we propose an alternative RGARCH model called the RGARCH-Exp model thatis more stable when dealing with outliers. We measure the performance of the volatility estimationby a loss function calculated using realized volatility as a proxy for true volatility and compare theRGARCH-type models with other asymmetric type models such as the EGARCH and GJR models.We conduct empirical studies of six stocks on the Tokyo Stock Exchange and find that a volatilityestimation using the RGARCH-type models outperforms the GARCH model and is comparable toother asymmetric GARCH models.