Showing 1 - 10 of 12
Persistent link: https://www.econbiz.de/10003920289
We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important...
Persistent link: https://www.econbiz.de/10012726170
We model a regression density flexibly so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important ways....
Persistent link: https://www.econbiz.de/10012746461
A general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate dependent mixture weights. The four parameters of the...
Persistent link: https://www.econbiz.de/10013147954
A general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate dependent mixture weights. The four parameters of the...
Persistent link: https://www.econbiz.de/10003896094
Smooth mixtures, i.e. mixture models with covariate-dependent mixing weights, are very useful flexible models for conditional densities. Previous work shows that using too simple mixture components for modeling heteroscedastic and/or heavy tailed data can give a poor fit, even with a large...
Persistent link: https://www.econbiz.de/10008696841
Persistent link: https://www.econbiz.de/10012179532
Smooth mixtures, i.e. mixture models with covariate-dependent mixing weights, are very useful flexible models for conditional densities. Previous work shows that using too simple mixture components for modeling heteroscedastic and/or heavy tailed data can give a poor fit, even with a large...
Persistent link: https://www.econbiz.de/10014188958
This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models such as Generalized Autoregressive Conditional...
Persistent link: https://www.econbiz.de/10014252427
While a large literature on return predictability has shown a link between valuation levels and expected rates of aggregate returns in-sample, we document a link between valuation levels and the shape of the distribution of cumulative (for example, over 12 and 24 months) total returns. Return...
Persistent link: https://www.econbiz.de/10012902527