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Forecasting Value-at-Risk and Expected Shortfall Using Fractionally Integrated Models of Conditional Volatility : International Evidence
Degiannakis, Stavros Antonios - 2018
forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …
Persistent link: https://www.econbiz.de/10012910119
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Value-at-risk and expected shortfall when there is long range dependence
Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2008
characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …
Persistent link: https://www.econbiz.de/10003636008
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A latent dynamic factor approach to forecasting multivariate stock market volatility : conference paper
Gribisch, Bastian - 2013
This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...
Persistent link: https://www.econbiz.de/10010341025
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Prediction of financial downside-risk with heavy-tailed conditional distributions
Mittnik, Stefan; Paolella, Marc S. - 2003
Persistent link: https://www.econbiz.de/10001788591
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Prediction of financial downside-risk with heavy-tailed conditional distributions
Mittnik, Stefan; Paolella, Marc S. - In: Handbook of heavy tailed distributions in finance, (pp. 385-404). 2003
Persistent link: https://www.econbiz.de/10001882139
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Prediction of financial downside-risk with heavy-tailed conditional distributions
Mittnik, Stefan; Paolella, Marc S. - 2003
The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...
Persistent link: https://www.econbiz.de/10009765347
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Factor structural time series models for official statistics with an application to hours worked in Germany
Weigand, Roland; Wanger, Susanne; Zapf, Ines - 2015
We introduce a high-dimensional structural time series model, where co-movement between the components is due to common factors. A two-step estimation strategy is presented, which is based on principal components in differences in a first step and state space methods in a second step. The...
Persistent link: https://www.econbiz.de/10011309972
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Optimizing time-series forecasts for inflation and interest rates using simulation and model averaging
Jumah, Adusei; Kunst, Robert M. - 2008
Motivated by economic-theory concepts - the Fisher hypothesis and the theory of the term structure - we consider a …
Persistent link: https://www.econbiz.de/10009735355
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Optimizing time-series forecasts for inflation and interest rates using simulation and model averaging
Jumah, Adusei; Kunst, Robert M. - 2008
Persistent link: https://www.econbiz.de/10003778880
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The impact of macroeconomic news on quote adjustments, noise, and informational volatility
Hautsch, Nikolaus; Hess, Dieter; Veredas, David - 2010
reflect information-driven and noise-induced volatilities. We find that all volatility components reveal distinct dynamics and … significantly declines thereafter. Moreover, news-affected responses in all volatility components are influenced by order flow … imbalances. -- efficient return ; macroeconomic announcements ; microstructure noise ; informational volatility …
Persistent link: https://www.econbiz.de/10003952800