Showing 1 - 10 of 137
High-dimensional regression problems which reveal dynamic behavior are typically analyzed by time propagation of a few number of factors. The inference on the whole system is then based on the low-dimensional time series analysis. Such highdimensional problems occur frequently in many different...
Persistent link: https://www.econbiz.de/10005677954
information in large sets of variables in vector autoregressive (VAR) models. This can be done by aggregating the variables or by … reducing the parameter space to a manageable dimension. Factor models reduce the space of variables whereas large Bayesian VAR …
Persistent link: https://www.econbiz.de/10010734524
In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...
Persistent link: https://www.econbiz.de/10005207936
This paper proposes a novel approach to the combination of conditional covariance matrix forecasts based on the use of the Generalized Method of Moments (GMM). It is shown how the procedure can be generalized to deal with large dimensional systems by means of a two-step strategy. The finite...
Persistent link: https://www.econbiz.de/10005207941
Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy …
Persistent link: https://www.econbiz.de/10005207944
We model the dynamic volatility and correlation structure of electricity futures of the European Energy Exchange index. We use a new multiplicative dynamic conditional correlation (mDCC) model to separate long-run from short-run components. We allow for smooth changes in the unconditional...
Persistent link: https://www.econbiz.de/10010607142
We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U.S., building on the Lee-Carter approach and extending it in several dimensions. We incorporate covariates and model their dynamics jointly with the latent variables underlying...
Persistent link: https://www.econbiz.de/10010609985
This paper investigates the finite sample properties of confidence intervals for structural vector error correction models (SVECMs) with long-run identifying restrictions on the impulse response functions. The simulation study compares methods that are frequently used in applied SVECM studies...
Persistent link: https://www.econbiz.de/10005677903
Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often 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...
Persistent link: https://www.econbiz.de/10005678005
(VAR) models. In advance, a principal components analysis (PCA) is adopted to reduce the dimensionality of the term … alternative implementations of the PCA/VAR model. This approach is shown to outperform forecasting schemes relying on global …
Persistent link: https://www.econbiz.de/10005678035