Titlebook: State-Space Models; Applications in Econ Yong Zeng,Shu Wu Book 2013 Springer Science+Business Media New York 2013 Econometrics.Macroeconomi

仪式

Parameter Estimation via Particle MCMC for Ultra-High Frequency Modelsmethods that are able to enhance the algorithm efficiency are discussed. Numerical studies through simulation and real data show that PMCMC method is able to yield reasonable estimates for model parameters.

Coordinate

The Extended Liu and West Filter: Parameter Learning in Markov Switching Stochastic Volatility Modeler takes advantage of recursive sufficient statistics that are sequentially tracked and whose behavior resembles that of a latent state with conditionally deterministic updates. The performance of the APF + SS filter is also assessed when exploring its sequential estimation of real data examples.

地牢

2199-093X wide range of subject areas from economics, finance, and st.State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book inc

思想流动

ALT

A Survey of Implicit Particle Filters for Data Assimilatione, even if the dimension of the state space is large. We explain how this idea is implemented, discuss special cases of practical importance, and work out the relations of the implicit particle filter with other data assimilation methods. We illustrate the theory with six examples.

Incompetent

A HMM Intensity-Based Credit Risk Model and Filteringdden dynamic frailty factor described by a hidden Markov chain. Filtering equations and filter-based estimates of the model, in recursive forms, are developed. We also give the joint default probability of reference entities in a credit portfolio as well as the variance dynamics for both observations and hidden states.

orthopedist

Book 2013 Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data.  The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals..

微粒

compassion

The State Space Representation and Estimation of a Time-Varying Parameter VAR with Stochastic Volatiof 2007–2009 was driven by a particularly bad shock to the unemployment rate which increased its trend and volatility substantially. In contrast, the impacts of the recession on the trend and volatility of nominal variables such as the core PCE inflation rate and the 10-year Treasury bond yield are

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A Statistical Investigation of Stock Return Decomposition Based on the State-Space Frameworkatio. In an effort to explore why this finding exists we employ a state-space modeling framework. We find that within this framework, it is the existence of weak identification combined with a small signal-to-noise ratio that leads to the conclusion that the data contains too little information for