Showing 1 - 10 of 124
prediction model specification methods, and that using “hybrid” combination factor/shrinkage methods often yields superior …-spread variables in nonlinear prediction model specification. …
Persistent link: https://www.econbiz.de/10011052271
This paper develops an indirect inference (Gourieroux et al., 1993; Smith, 1993) estimation method for a large class of dynamic equilibria. Our approach consists of constructing econometrically tractable auxiliary equilibria, obtained by simplifying the economic primitives of the structural...
Persistent link: https://www.econbiz.de/10011190714
We extend the asymmetric, stochastic, volatility model by modeling the return-volatility distribution nonparametrically. The novelty is modeling this distribution with an infinite mixture of Normals, where the mixture unknowns have a Dirichlet process prior. Cumulative Bayes factors show our...
Persistent link: https://www.econbiz.de/10010730133
. The new method is applied to two forecasting problems in econometrics: equity premium prediction and inflation forecasting …
Persistent link: https://www.econbiz.de/10010730145
This paper introduces a new family of portmanteau tests for serial correlation. Using the wavelet transform, we decompose the variance of the underlying process into the variance of its low frequency and of its high frequency components and we design a variance ratio test of no serial...
Persistent link: https://www.econbiz.de/10011077599
This paper introduces the concept of risk parameter in conditional volatility models of the form ϵt=σt(θ0)ηt and develops statistical procedures to estimate this parameter. For a given risk measure r, the risk parameter is expressed as a function of the volatility coefficients θ0 and the...
Persistent link: https://www.econbiz.de/10011077602
GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks in the volatility process. Flexible alternatives are Markov-switching GARCH and change-point GARCH models. They require estimation by MCMC methods due to the path dependence problem. An unsolved...
Persistent link: https://www.econbiz.de/10011052313
A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of...
Persistent link: https://www.econbiz.de/10010588322
We consider a method for producing multivariate density forecasts that satisfy moment restrictions implied by economic theory, such as Euler conditions. The method starts from a base forecast that might not satisfy the theoretical restrictions and forces it to satisfy the moment conditions using...
Persistent link: https://www.econbiz.de/10011052219
We propose new methods for evaluating predictive densities. The methods include Kolmogorov–Smirnov and Cramér–von Mises-type tests for the correct specification of predictive densities robust to dynamic mis-specification. The novelty is that the tests can detect mis-specification in the...
Persistent link: https://www.econbiz.de/10011052231