Modeling long memory volatility using realized measures of volatility: A realized HAR GARCH model |
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| Institution: | 1. National School of Development, Peking University, Beijing, China;2. School of Banking and Finance, University of International Business and Economics, Beijing, China;1. Institute of Economic Studies, Charles University in Prague, Opletalova 26, 110 00 Prague, Czech Republic;2. Institute of Information Theory and Automation, Czech Academy of Sciences, Pod Vodarenskou Vezi 4, 182 00 Prague, Czech Republic;1. Financial Engineering Research Unit, Department of Management Science and Technology, Athens University of Economics and Business, 47A Evelpidon Str., 11362 Athens, Greece;2. Bank of Greece, Financial Stability Department, 3 Amerikis Str., 105 64 Athens, Greece |
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| Abstract: | Long memory is an important feature of the volatility of financial returns. We document that the recently developed Realized GARCH model (Hansen et al., 2012) is insufficient for capturing the long memory of underlying volatility. We develop a parsimonious variant of the Realized GARCH model by introducing the HAR specification of Corsi (2009) into the volatility dynamics. A comparison of the theoretical and sample autocorrelation functions shows that the new model specification better captures the long memory dynamics of volatility. We calculate the multi-period out-of-sample volatility forecasts for several return series and find that the new model is a significant improvement over the classic Realized GARCH model. |
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