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Volatility estimation using a rational GARCH model

Hiroshima University of Economics, 731-0192, Gion, Asaminami-ku, Hiroshima, Japan

Special Issues: Volatility of Prices of Financial Assets

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.
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Keywords asymmetric volatility; rational GARCH model; bayesian inference; Markov ChainMonte Carlo; Metropolis-Hastings algorithm; realized volatility; Padé approximants; student-tdistribution; QLIKE loss function

Citation: Tetsuya Takaishi. Volatility estimation using a rational GARCH model. Quantitative Finance and Economics, 2018, 2(1): 127-136. doi: 10.3934/QFE.2018.1.127


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