Nonlinear Kalman Filtering in Affine Term Structure Models

Non-Linear Filtering in the Estimation of a Term Structure Model of Interest Rates

The methods of the class of Kalman filters have recently been used in the estimation of the term structure of interest rates. These methods can employ both time-series and cross-sectional aspects of term structure models. This paper compares the performance of two kinds of non-linear Kalman filter algorithms Extended Kalman Filter (EKF) and Square-Root Unscented Kalman Filter (SRUKF) in estimat...

On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR

Extended Kalman Filtering (EKF) is a nonlinear dynamic data reconciliation (NDDR) method. One of its main advantages is its suitability for on-line applications. This paper presents an on-line NDDR method using EKF. It is implemented for two case studies, temperature measurements of a distillation column and concentration measurements of a CSTR. In each time step, random numbers with zero m...

Application of the Kalman-Bucy filter in the stochastic differential equation for the modeling of RL circuit

In this paper, we present an application of the stochastic calculusto the problem of modeling electrical networks. The filtering problem have animportant role in the theory of stochastic differential equations(SDEs). In thisarticle, we present an application of the continuous Kalman-Bucy filter for a RLcircuit. The deterministic model of the circuit is replaced by a stochastic model byadding a ...

Cross sectional efficient estimation of stochastic volatility short rate models

We consider the problem of estimation of term structure of interest rates. Filtering theory approach is very natural here with the underlying setup being non-linear and non-Gaussian. Earlier works make use of Extended Kalman Filter (EKF). However, as indicated by de Jong (2000), the EKF in this situation leads to inconsistent estimation of parameters, though without high bias. One way to avoid ...

application of affine gray-box neural models for nonlinear control of chemical processes