We introduce a new multivariate stochastic volatility model, based on the presence of a latent common factor with random jumps. The common factor is parameterized as a permanent component using a compound binomial process. This model can capture common jumps in the latent volatilities between...

In this article we introduce a new methodology for modeling curves with a dynamic structure, using a non-parametric approach formulated as a state space model. The non-parametric approach is based on the use of penalized splines, represented as a dynamic mixed model. This formulation can capture...

In this paper we analyze a maximum likelihood estimator using data cloning for stochastic volatility models.This estimator is constructed using a hybrid methodology based on Integrated Nested Laplace Approximations to calculate analytically the auxiliary Bayesian estimators with great accuracy...

This paper assesses the relation between the yield curve and the main macroeconomic variables in the U.S. between early 1970s and 2000. We revisit the macro-finance model of Diebold et al. (2006) with the inclusion of a stochastic volatility structure for the latent factors and macroeconomic...

This work proposes the application of a stochastic volatility model with jumps to the BRL/USD exchange rate. This model decomposes the process into transitory and permanent components that capture the jumps in the level of the unobserved volatility process. The model estimation is done using...