Download or read book Modeling and Estimation of Synchronization in Multistate Markov switching Models written by Cem Cakmakli and published by . This book was released on 2011 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling and Estimation of Synchronisation in Multistate Markov switching Models written by Çem Cakmakli and published by . This book was released on 2011 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Synchronization of Markov Chains in Multivariate Regime Switching Models written by Raphael Vial and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate regime-switching presents an efficient way of jointly modeling the cyclical behavior of financial time series. Standard regime-switching models thereby a priori determine the relationship between the regime-switches of individual assets. These switches are usually assumed to be either perfectly synchronized or fully independent. However, neither assumption seems realistic in practice. This thesis develops a multivariate Markov regime-switching model to infer the actual degree of synchronization from the underlying data. This flexible model allows subgroups of assets to be driven by individual Markov chains. At the same time, these Markov chains underlie a dynamically changing degree of synchronization. In comparison to most existing solutions, this model is not restricted to bivariate analysis. To keep the model traceable, a novel factorization algorithm for the regime-dependent correlation matrix is formulated. This algorithm scales down the increase in parameters and presents an efficient way of ensuring positive semi-definite correlation matrices. The structure of the flexible regime-switching model is motivated by the initial synchronization analysis conducted in this thesis. The analysis of univariate regime-switching results shows that neither perfectly synchronized nor fully independent regime cycles are empirically observable. The synchronization of regime cycles tends to dynamically change over time. Some assets, however, might show more contemporaneous switching dynamics and can therefore be governed by a joint regime process. The empirical results for a sample of six international equity markets confirm the assumptions underlying this thesis. The flexible model reveals a stable synchronization factor, marked by one particular change in synchronization. The estimated parameters of this model closely cover the individual dynamics of their underlying assets and confirm the model's validity. Moreover, in some.

Download or read book How Well Do Markov Switching Models Describe Actual Business Cycles written by Penelope A. Smith and published by . This book was released on 2004 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Markov Switching Multi fractal Model of Asset Returns written by Hwa Taek Lee and published by . This book was released on 2007 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Basic Recursion for Markov Switching Models written by Lung-Fei Lee and published by . This book was released on 1995 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Explicit duration Markov Switching Models written by Silvia Chiappa and published by . This book was released on 2014 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov switching models (MSMs) are probabilistic models that employ multiple sets of parameters to describe different dynamic regimes that a time series may exhibit at different periods of time. The switching mechanism between regimes is controlled by unobserved random variables that form a first-order Markov chain. Explicit-duration MSMs contain additional variables that explicitly model the distribution of time spent in each regime. This allows to define duration distributions of any form, but also to impose complex dependence between the observations and to reset the dynamics to initial conditions. Models that focus on the first two properties are most commonly known as hidden semi-Markov models or segment models, whilst models that focus on the third property are most commonly known as changepoint models or reset models. In this monograph, we provide a description of explicit-duration modelling by categorizing the different approaches into three groups, which differ in encoding in the explicit-duration variables different information about regime change/reset boundaries. The approaches are described using the formalism of graphical models, which allows to graphically represent and assess statistical dependence and therefore to easily describe the structure of complex models and derive inference routines. The presentation is intended to be pedagogical, focusing on providing a characterization of the three groups in terms of model structure constraints and inference properties. The monograph is supplemented with a software package that contains most of the models and examples described. The material presented should be useful to both researchers wishing to learn about these models and researchers wishing to develop them further.

Download or read book Macroeconometrics and Time Series Analysis written by Steven Durlauf and published by Springer. This book was released on 2016-04-30 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.

Download or read book Incorporating Vintage Differences and Forecasts Into Markov Switching Models written by Jeremy Nalewaik and published by . This book was released on 2007 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Markov Regime switching Models written by Lingyun Ye and published by . This book was released on 2012 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: A regime-switching model is a time-series model in which parameters change values according to the regime at present time. While regime-switching models have been very popular in applied work, there is a lack of literature for simulation studies. New methods based on regime-switching models are often proposed with neither a proof of convergence nor simulations to demonstrate their basic properties. In this thesis, a detailed simulation study of regime-switching models is conducted. A strategy to generate initial search values in the parameter estimation of regime-switching models is proposed. It is shown that this method can dramatically reduce the number of restarts of the optimizer. Even in 3-regime models (with 15 unknown parameters), parameters can be estimated reasonably well with only 5 restarts.

Download or read book Time Varying Transition Probabilities for Markov Regime Switching Models written by Marco Bazzi and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new Markov switching model with time-varying transitions probabilities. The novelty of our model is that the transition probabilities evolve over time by means of an observation driven model. The innovation of the time-varying probability is generated by the score of the predictive likelihood function. We show how the model dynamics can be readily interpreted. We investigate the performance of the model in a Monte Carlo study and show that the model is successful in estimating a range of different dynamic patterns for unobserved regime switching probabilities. We also illustrate the new methodology in an empirical setting by studying the dynamic mean and variance behaviour of US industrial production growth.

Download or read book Time Varying Transition Probabilities for Markov Regime Switching Models written by Marco Bazzi and published by . This book was released on 2014 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new Markov switching model with time varying probabilities for the transitions. The novelty of our model is that the transition probabilities evolve over time by means of an observation driven model. The innovation of the time varying probability is generated by the score of the predictive likelihood function. We show how the model dynamics can be readily interpreted. We investigate the performance of the model in a Monte Carlo study and show that the model is successful in estimating a range of different dynamic patterns for unobserved regime switching probabilities. We also illustrate the new methodology in an empirical setting by studying the dynamic mean and variance behavior of U.S. Industrial Production growth. We find empirical evidence of changes in the regime switching probabilities, with more persistence for high volatility regimes in the earlier part of the sample, and more persistence for low volatility regimes in the later part of the sample.

Download or read book Analytical Derivatives for Markov Switching Models written by Jeff Gable and published by . This book was released on 2008 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper derives analytical gradients for a broad class of regime-switching models with Markovian state-transition probabilities. Such models are usually estimated by maximum likelihood methods, which require the derivatives of the likelihood function with respect to the parameter vector. These gradients are usually calculated by means of numerical techniques. The paper shows that analytical gradients considerably speed up maximum-likelihood estimation with no loss in accuracy. A sample program listing is included.

Download or read book The New Palgrave Dictionary of Economics written by and published by Springer. This book was released on 2016-05-18 with total page 7493 pages. Available in PDF, EPUB and Kindle. Book excerpt: The award-winning The New Palgrave Dictionary of Economics, 2nd edition is now available as a dynamic online resource. Consisting of over 1,900 articles written by leading figures in the field including Nobel prize winners, this is the definitive scholarly reference work for a new generation of economists. Regularly updated! This product is a subscription based product.

Download or read book Model Selection and Some Extensions of Markov Switching Models written by Jing Zhang and published by . This book was released on 1998 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Markov Switching Models for Volatility written by Monica Billio and published by . This book was released on 2013 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is devoted to show duality in the estimation of Markov Switching (MS) processes for volatility. It is well-known that MS-GARCH models suffer of path dependence which makes the estimation step unfeasible with usual Maximum Likelihood procedure. However, by rewriting the MS-GARCH model in a suitable linear State Space representation, we are able to give a unique framework to reconcile the estimation obtained by the Kalman Filter and with some auxiliary models proposed in the literature. Reasoning in the same way, we present a linear Filter for MS-Stochastic Volatility (MS-SV) models on which different conditioning sets yield more flexibility in the estimation. Estimation on simulated data and on short-term interest rates shows the feasibility of the proposed approach.

Download or read book State space Models with Regime Switching written by Chang-Jin Kim and published by Mit Press. This book was released on 1999 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.