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Forecasting euro-area variables with German pre-EMU data
Brüggemann, Ralf; Lütkepohl, Helmut; Marcellino, … - 2006
period 1970Q1 - 2003Q4 for ten macroeconomic variables. The years 2000 - 2003 are used as forecasting period. A range of … different univariate forecasting methods is applied. Some of them are based on linear autoregressive models and we also use some … forecasting variables which need considerable adjustments in their levels when joining German and EMU data. These results suggest …
Persistent link: https://www.econbiz.de/10010263654
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Testing directional forecast value in the presence of serial correlation
Blaskowitz, Oliver J.; Herwartz, Helmut - 2008
Common approaches to test for the economic value of directional forecasts are based on the classical Chi-square test for independence, Fisher’s exact test or the Pesaran and Timmerman (1992) test for market timing. These tests are asymptotically valid for serially independent observations....
Persistent link: https://www.econbiz.de/10010271838
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Local adaptive multiplicative error models for high-frequency forecasts
Härdle, Wolfgang Karl; Hautsch, Nikolaus; Mihoci, Andrija - 2012
modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM …
Persistent link: https://www.econbiz.de/10010330969
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Multivariate volatility modeling of electricity futures
Bauwens, Luc; Hafner, Christian M.; Pierret, Diane - 2011
new model achieves higher forecasting performance compared to a standard DCC model. …
Persistent link: https://www.econbiz.de/10010330971
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Adaptive order flow forecasting with multiplicative error models
Härdle, Wolfgang Karl; Mihoci, Andrija; Ting, … - 2014
A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading...
Persistent link: https://www.econbiz.de/10010427064
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Varying coefficient GARCH versus local constant volatility modeling. Comparison of the predictive power
Polzehl, Jörg; Spokoiny, Vladimir - Sonderforschungsbereich Ökonomisches Risiko <Berlin>
GARCH models are widely used in financial econometrics. However, we show by mean of a simple simulation example that the GARCH approach may lead to a serious model misspecification if the assumption of stationarity is violated. In particular, the well known integrated GARCH effect can be...
Persistent link: https://www.econbiz.de/10005854708
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Stochastic PopulationForecast for Germany and itsConsequence for the GermanPension System
Härdle, Wolfgang; Mysickova, Alena - Sonderforschungsbereich Ökonomisches Risiko <Berlin> - 2009
Population forecasts are crucial for many social, political and economic decisions. Officialpopulation projections rely in general on deterministic models which use different scenariosfor future vital rates to indicate uncertainty. However, this technique shows substantialweak points such as...
Persistent link: https://www.econbiz.de/10008939790
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Copula dynamics in CDOs
Choros-Tomczyk, Barbara; Härdle, Wolfgang Karl; … - 2012
Values of tranche spreads of collateralized debt obligations (CDOs) are driven by the joint default performance of the assets in the collateral pool. The dependence between the names in the portfolio mainly depends on current economic conditions. Therefore, a correlation implied from tranches...
Persistent link: https://www.econbiz.de/10010318769
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Varying coefficient GARCH versus local constant volatility modeling: Comparison of the predictive power
Polzehl, Jörg; Spokoiny, Vladimir - 2006
locally constant model from Polzehl and Spokoiny (2002) by means of simulated and real data sets using different forecasting … GARCH(1,1) model also demonstrates a relatively good forecasting performance as far as the short term forecasting horizon is … considered. However, its application to long term forecasting seems questionable because of possible misspecification of the …
Persistent link: https://www.econbiz.de/10010265657
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Predicting extreme VaR: Nonparametric quantile regression with refinements from extreme value theory
Schaumburg, Julia - 2010
extreme value theory. The out-of-sample forecasting performance of our methods turns out to be clearly superior to different …
Persistent link: https://www.econbiz.de/10010270817