Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons

Turgut Kisinbay

No 2003/131, IMF Working Papers from International Monetary Fund

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.

Keywords: WP; EGARCH model; high frequency; TARCH model; null hypothesis; GARCH; high-frequency data; realized volatility; integrated volatility; and asymmetric volatility; GARCH model; benchmark model; APARCH model; JPY dataset; standard deviation; volatility model; Asset prices; Stock markets; Stocks (search for similar items in EconPapers)
Pages: 38
Date: 2003-06-01
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Citations: View citations in EconPapers (4)

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Journal Article: Predictive ability of asymmetric volatility models at medium-term horizons (2010)
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