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Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons

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  • Turgut Kisinbay

Abstract

Using 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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  • Turgut Kisinbay, 2003. "Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons," IMF Working Papers 2003/131, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2003/131
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    3. Dimitrios P. Louzis & Spyros Xanthopoulos-Sisinis & Apostolos P. Refenes, 2012. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Applied Economics, Taylor & Francis Journals, vol. 44(27), pages 3533-3550, September.
    4. Raj Kumar Singh & Yashvardhan Singh & Satish Kumar & Ajay Kumar & Waleed S. Alruwaili, 2024. "Mapping Risk–Return Linkages and Volatility Spillover in BRICS Stock Markets through the Lens of Linear and Non-Linear GARCH Models," JRFM, MDPI, vol. 17(10), pages 1-26, September.

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