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A Spectral Hidden Markov Model for Nonstationary Oscillatory Processes
We propose to model time-varying periodic and oscillatory processes by m...
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Estimation of Markovian-regime-switching models with independent regimes
Markovian-regime-switching (MRS) models are commonly used for modelling ...
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Visual analytics for team-based invasion sports with significant events and Markov reward process
In team-based invasion sports such as soccer and basketball, analytics i...
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Inference of Binary Regime Models with Jump Discontinuities
We have developed a statistical technique to test the model assumption o...
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Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models
In this paper, we consider a variety of multi-state Hidden Markov models...
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Improve Orthogonal GARCH with Hidden Markov Model
Orthogonal Generalized Autoregressive Conditional Heteroskedasticity mod...
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Pricing Energy Contracts under Regime Switching Time-Changed models
The shortcomings of the popular Black-Scholes-Merton (BSM) model have le...
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Bayesian nonparametric panel Markov-switching GARCH models
This paper introduces a new model for panel data with Markov-switching GARCH effects. The model incorporates a series-specific hidden Markov chain process that drives the GARCH parameters. To cope with the high-dimensionality of the parameter space, the paper exploits the cross-sectional clustering of the series by first assuming a soft parameter pooling through a hierarchical prior distribution with two-step procedure, and then introducing clustering effects in the parameter space through a nonparametric prior distribution. The model and the proposed inference are evaluated through a simulation experiment. The results suggest that the inference is able to recover the true value of the parameters and the number of groups in each regime. An empirical application to 78 assets of the SP&100 index from 6^th January 2000 to 3^rd October 2020 is also carried out by using a two-regime Markov switching GARCH model. The findings shows the presence of 2 and 3 clusters among the constituents in the first and second regime, respectively.
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