Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons
June 1, 2003
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Summary
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.
Subject: Asset prices, Economic forecasting, Financial institutions, Financial markets, Foreign exchange, Prices, Stock markets, Stocks
Keywords: and asymmetric volatility, APARCH model, Asset prices, benchmark model, EGARCH model, GARCH, GARCH model, high frequency, high-frequency data, integrated volatility, JPY dataset, null hypothesis, realized volatility, standard deviation, Stock markets, Stocks, TARCH model, volatility model, WP
Pages:
38
Volume:
2003
DOI:
Issue:
131
Series:
Working Paper No. 2003/131
Stock No:
WPIEA1312003
ISBN:
9781451855302
ISSN:
1018-5941
