Markov-switching GARCH models
Markov-switching GARCH models in finance: a unifying framework with an application to the German stock market
... of Markov-switching GARCH models to commoditiy prices, stock returns and exchange-rate return data are presented, inter alia, in Alizadeh et ...two-regime Markov-switching ...
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Markov Switching GARCH Models: Filtering, Approximations and Duality
... one. Models which elude in this way the path dependence problem are proposed by [14], [10] and [18], among others, and are known as collapsing proce- ...MS GARCH models has been proposed by [15] for ...
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Markov Switching Garch Models of Currency Crises in Southeast Asia
... selected models for ...the Markov probabilities are ...The GARCH parameters, α and β, are statistically well-deÞned and in line with the values reported in the literature on exchange rate ...
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Active portfolio management in the Andean countries’ stock markets with Markov-Switching GARCH models
... The Econometric application of these studies has been done in several developed countries such as the European Monetary Union countries or in specific countries such as France, Germany, Japan, Switzerland, the United ...
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Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models
... of Markov-Switching (MS) models with time-fixed or Generalized Autoregressive Conditional Heteroskedasticity (GARCH) ...MS-GARCH models and VIX futures leads the simulated ...
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Regime switching behavior of volatilities of Islamic equities: evidence from Markov Switching GARCH models for some selected broad based indices
... regime switching behavior of some selected broad based Islamic equity indices around the ...MSGARCH models was mainly employed for the ...regime switching tendency between the two regimes are very ...
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Marginal likelihood for Markov-switching and change-point GARCH models
... The path dependence problem occurs because the conditional variance at time t depends on the entire sequence of regimes visited up to time t, due to the recursive nature of the GARCH process. Since the regimes are ...
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Marginal Likelihood for Markov-Switching and Change-Point Garch Models
... The path dependence problem occurs because the conditional variance at time t depends on the entire sequence of regimes visited up to time t, due to the recursive nature of the GARCH process. Since the regimes are ...
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Marginal Likelihood for Markov-Switching and Change-Point GARCH Models
... CP-GARCH models are flexible alternatives to GARCH models with fixed parame- ...such models in integrating the latent state variables that govern the parameter evolution between ...
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Theory and Inference for a Markov-Switching GARCH Model
... of models is certainly that of GARCH models (see ...These models usually indicate a high persistence of the conditional variance ...a GARCH model on a sample displaying structural ...
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Theory and inference for a Markov switching Garch model.
... of models is certainly that of GARCH models (see ...These models usually indicate a high persistence of the conditional variance ...a GARCH model on a sample displaying structural ...
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Theory and inference for a Markov switching GARCH model
... of models is certainly that of GARCH models (see ...These models usually indicate a high persistence of the conditional variance ...a GARCH model on a sample displaying structural ...
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Regime switching GARCH models
... several models that are based on a mixture of distributions have been ...a GARCH to avoid the problem of path dependence of the conditional volatility on the ruling ...tractable ...
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Regime switching GARCH models
... several models that are based on a mixture of distributions have been ...a GARCH to avoid the problem of path dependence of the conditional volatility on the ruling ...tractable ...
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Probabilistic properties of a Markov-switching periodic $GARCH$ process
... periodic GARCH (P GARCH) models introduced by Bollerslev and Ghysels [16] has shown to be appropriate for capturing periodicity in the conditional variance, a property that cannot be explained by the ...
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Modeling Markov Switching ARMA-GARCH Neural Networks Models and an Application to Forecasting Stock Returns
... nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH ...type models with artificial neural networks to benefit from the universal ...
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Performance of Markov Switching GARCH Model Forecasting Inflation Uncertainty
... a Markov regime-switching GARCH model, one with normally distributed errors (MS-GARCH-N) and another with t-distributed errors (MS-GARCH-t), and compare their relative in-sample as well ...
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Markov switching in GARCH processes and mean reverting stock market volatility
... volatility models should aim to ...volatility models, notably generalized autoregressive conditional heteroskedasticity IGARCH, Bollerslev (1986)], find hard to reconcile are: 1) conditional volatility can ...
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Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models
... Component GARCH (CGARCH) variant made it optimal for modelling the conditional variance of ...single-regime GARCH model is suitable for capturing the price risk of a cryptocurrency is simply ...
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Particle Filters for Markov Switching Stochastic Volatility Models
... and GARCH family of models for short-term interest ...a Markov switching stochastic volatility (MSSV) model to measure the fluctuations in volatility according to economic ...
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