In this paper we present a stochastic volatility model assuming that the return shock has a Skew-GED distribution. This allows a parsimonious yet flexible treatment of asymmetry and heavy tails in the conditional distribution of returns. The Skew-GED distribution nests both the GED, the Skew-normal and the normal densities as special cases so that specification tests are easily performed. Inference is conducted under a Bayesian framework using Markov Chain MonteCarlo methods for computing the posterior distributions of the parameters. More precisely, our Gibbs-MH updating scheme makes use of the Delayed Rejection Metropolis-Hastings methodology as proposed by Tierney and Mira (1999), and of Adaptive-Rejection Metropolis sampling. We apply t...
It has long been recognised that the return volatility of financial assets tends to vary over time w...
Abstract: This paper extends the existing fully parametric Bayesian literature on stochastic volatil...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
In this paper we present a stochastic volatility model assuming that the return shock has a Skew-GED...
While the time-varying volatility of financial returns has been extensively modelled, most existing ...
This study provides empirical evidence on asymmetry in financial returns using a simple stochastic v...
This study provides empirical evidence on asymmetry in financial returns using a simple stochastic v...
Bayesian analysis of a stochastic volatility model with a generalized hyperbolic (GH) skew Student’s...
Bayesian analysis of a stochastic volatility model with a generalized hyperbolic (GH) skew Student’s...
This paper examines two asymmetric stochastic volatility mod-els used to describe the heavy tails an...
This paper proposes a novel simulation-based inference for an asymmetric stochastic volatility model...
This thesis introduces a generalization of the Threshold Stochastic Volatility (THSV) model proposed...
December 19, 2009Bayesian analysis of a stochastic volatility model with a generalized hyperbolic (G...
In stochastic volatility (SV) models, asset returns conditional on the latent volatility are usually...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
It has long been recognised that the return volatility of financial assets tends to vary over time w...
Abstract: This paper extends the existing fully parametric Bayesian literature on stochastic volatil...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
In this paper we present a stochastic volatility model assuming that the return shock has a Skew-GED...
While the time-varying volatility of financial returns has been extensively modelled, most existing ...
This study provides empirical evidence on asymmetry in financial returns using a simple stochastic v...
This study provides empirical evidence on asymmetry in financial returns using a simple stochastic v...
Bayesian analysis of a stochastic volatility model with a generalized hyperbolic (GH) skew Student’s...
Bayesian analysis of a stochastic volatility model with a generalized hyperbolic (GH) skew Student’s...
This paper examines two asymmetric stochastic volatility mod-els used to describe the heavy tails an...
This paper proposes a novel simulation-based inference for an asymmetric stochastic volatility model...
This thesis introduces a generalization of the Threshold Stochastic Volatility (THSV) model proposed...
December 19, 2009Bayesian analysis of a stochastic volatility model with a generalized hyperbolic (G...
In stochastic volatility (SV) models, asset returns conditional on the latent volatility are usually...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
It has long been recognised that the return volatility of financial assets tends to vary over time w...
Abstract: This paper extends the existing fully parametric Bayesian literature on stochastic volatil...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...