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over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel …
Persistent link: https://www.econbiz.de/10010250513
This paper proposes efficient estimators of risk measures in a semiparametric GARCH model defined through moment …
Persistent link: https://www.econbiz.de/10009620388
for main indices from stock exchanges was conducted. The VaR forecasts from GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH … volatility trend. However, GARCH-st (1,1) and QML-GARCH(1,1) were found to be the most robust models in the different volatility …
Persistent link: https://www.econbiz.de/10011967246
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011730304
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011674479
In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical...
Persistent link: https://www.econbiz.de/10012292347
The theory suggests that investment activities and monetary policy influence the development of the global business cycle. The oil price and other raw material prices also play a key role in the economic development and there is a co-movement among oil consumption and global output. Therefore,...
Persistent link: https://www.econbiz.de/10009736654
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