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Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons, 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
Language
eng
Literary Form
non fiction
Note
Bibliographic Level Mode of Issuance: Monograph
Physical Description
1 online resource (38 pages)
Form Of Item
online
Isbn
9786613800657

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