The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models since they require the updating of a function. The aim of this paper is to consider the situation of a large number n of individual measurements, called...

The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models since they require the updating of a function. The aim of this paper is to consider the situation of a large number n of individual measurements, called...

The class of parametric dynamic latent variable models is becoming increasingly popular in finance and economics. Latent factor models, switching regimes models, stochastic volatility models, and dynamic disequilibrium models are only a few examples of this class of model. Inference in this...

The purpose of this article is to propose a global discrete-time modeling of the term structure of interest rates which is able to capture simultaneously the following important features: (i) a historical dynamics of the factor driving term structure shapes involving several lagged values, and...

This article presents a general discrete-time affine framework aimed at jointly modeling yield curves associated with different debtors. The underlying fixed-income securities may differ in terms of credit quality and/or in terms of liquidity. The risk factors follow conditionally Gaussian...