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In this paper we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. Its novelty is in modeling the joint, conditional,...
Persistent link: https://www.econbiz.de/10010555040
In this paper, we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. Its novelty is in modeling the joint, conditional,...
Persistent link: https://www.econbiz.de/10010292350
methods, which provide mixing over both the location and scale of the normal components. MCMC methods are introduced for …
Persistent link: https://www.econbiz.de/10010292242
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
methods which provide mixing over both the location and scale of the normal components. MCMC methods are introduced for …
Persistent link: https://www.econbiz.de/10010850125
This paper extends the existing fully parametric Bayesian literature on stochastic volatility to allow for more general return distributions. Instead of specifying a particular distribution for the return innovation, we use nonparametric Bayesian methods to flexibly model the skewness and...
Persistent link: https://www.econbiz.de/10010292240
We present an estimation and forecasting method, based on a differential evolution MCMC method, for inference in GARCH …
Persistent link: https://www.econbiz.de/10011116269
Understanding how defaults correlate across firms is a persistent concern in risk management. In this paper, we apply covariate-dependent copula models to assess the dynamic nature of credit risk dependence, which we define as "credit risk clustering". We also study the driving forces of the...
Persistent link: https://www.econbiz.de/10012657552
Understanding how defaults correlate across firms is a persistent concern in risk management. In this paper, we apply covariate-dependent copula models to assess the dynamic nature of credit risk dependence, which we define as "credit risk clustering". We also study the driving forces of the...
Persistent link: https://www.econbiz.de/10012024047
The time-series dynamics of short-term interest rates are important as they are a key input into pricing models of the term structure of interest rates. In this paper we extend popular discrete time short-rate models to include Markov switching of infinite dimension. This is a Bayesian...
Persistent link: https://www.econbiz.de/10011185700