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The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility
Clark, Todd E.; Ravazzolo, Francesco - 2012
Persistent link: https://www.econbiz.de/10009627354
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The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility
Clark, Todd E.; Ravazzolo, Francesco - 2012
Persistent link: https://www.econbiz.de/10009628606
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Small sample properties of forecasts from autoregressive models under structural breaks
Timmermann, Allan; Pesaran, M. Hashem - 2003
Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...
Persistent link: https://www.econbiz.de/10011508088
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Long memory with Markov-Switching GARCH
Krämer, Walter (contributor) - 2008
Persistent link: https://www.econbiz.de/10003641700
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On the origins of high persistence in GARCH-models
Krämer, Walter; Tameze Azamo, Baudouin; Christou, … - 2009
Persistent link: https://www.econbiz.de/10008839631
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l 1 - penalized likelihood smoothing of volatility processes allowing for abrupt changes
Neto, David; Sardy, Sylvain; Tseng, Paul - 2009
Persistent link: https://www.econbiz.de/10003926975
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Can the Lasota (1977)'s model compete with the Mackey-Glass (1977)'s model in nonlinear modelling of financial time series?
Hennani, Rachida - 2015
Persistent link: https://www.econbiz.de/10011300800
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Herding, a-synchronous updating and heterogeneity in memory in a CBS
Diks, Cees G. H.; Weide, Roy van der - 2003
predicts MA(1) structure with a negative coeffient. Asynchronous updating leads to an MA(1) model for returns with GARCH($1 …,1$) innovations, and predicts a relation between the ARCH and GARCH coefficients. Heterogeneity in memory leads to long … coefficient and the relation between the ARCH and GARCH coefficients for exchange rate data. …
Persistent link: https://www.econbiz.de/10011334332
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Why frequency matters for unit root testing
Boswijk, Herman Peter; Klaassen, Franc - 2004 - Rev.
It is generally believed that for the power of unit root tests, only the time span and not the observation frequency matters. In this paper we show that the observation frequency does matter when the high-frequency data display fat tails and volatility clustering, as is typically the case for...
Persistent link: https://www.econbiz.de/10011342578
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Stock index volatility forecasting with high frequency data
Hol Uspensky, Eugenie; Koopman, Siem Jan - 2002
Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …
Persistent link: https://www.econbiz.de/10011326944