Predictive ability of asymmetric volatility models at medium-term horizons
AbstractUsing realized volatility to estimate conditional variance of financial returns, we compare forecasts of volatility from linear GARCH models with asymmetric ones. We consider horizons extending to 30 days. Forecasts are compared using three different evaluation tests. With data from an equity index and two foreign exchange returns, we show that asymmetric models provide statistically significant forecast improvements upon the GARCH model for two of the datasets and improve forecasts for all datasets by means of forecasts combinations. These results extend to about 10 days in the future, beyond which the forecasts are statistically inseparable from each other.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 42 (2010)
Issue (Month): 30 ()
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- Turgut Kisinbay, 2003. "Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons," IMF Working Papers 03/131, International Monetary Fund.
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