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Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence From Markov‐Switching Multifractal Models

Journal of Forecasting, Volume 45, Issue 6, Page 2905-2941, September 2026.
ABSTRACT This paper adopts a bivariate Markov‐switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio
Ruipeng Liu, Mawuli Segnon, Oguzhan Cepni, Rangan Gupta   +3 more
wiley   +1 more source

Brain state and dynamic transition patterns of motor imagery revealed by the bayes hidden markov model. [PDF]

Cogn Neurodyn
Liu Y, Yu S, Li J, Ma J, Wang F, Sun S, Yao D, Xu P, Zhang T.   +8 more
europepmc   +1 more source

An intelligent model to decode students' behavioral states in physical education using back propagation neural network and Hidden Markov Model. [PDF]

BMC Psychol
Li L.
europepmc   +1 more source

ResFungi: A Novel Protein Database of Antifungal Drug Resistance Genes Using a Hidden Markov Model Profile. [PDF]

ACS Omega
Santana de Carvalho D, Bastos RW, Rossato L, Teixeira de Aguiar Peres N, Assis Santos D.   +4 more
europepmc   +1 more source

Utilizing profile hidden Markov model databases for discovering viruses from metagenomic data: a comprehensive review. [PDF]

Brief Bioinform
Yu R, Huang Z, Lam TYC, Sun Y.
europepmc   +1 more source

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Markov models — hidden Markov models

Nature Methods, 2019
“Everything we see hides another thing, we always want to see what is hidden by what we see” — Rene ...
Jasleen K. Grewal, Martin Krzywinski, Naomi Altman   +2 more
openaire   +1 more source

Nonstationary hidden Markov model

Signal Processing, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
SIN, B, KIM, JH Kim, JinHyung
openaire   +3 more sources

Ergodicity of hidden Markov models

Mathematics of Control, Signals, and Systems, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Giovanni B. Di Masi, Lukasz Stettner
openaire   +2 more sources

Contextual Hidden Markov Models

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
Multiple works have proposed extensions of HMMs for handling variability. We focus here on the design of HMMs whose probability distribution on sequences depends on additional external variables that we call the context, which may stand for emotion features in speech recognition, physical features in gesture recognition, etc. We show experimentally the
Radenen, Mathieu, Artières, Thierry
openaire   +1 more source

Partially hidden Markov models

IEEE Transactions on Information Theory, 1996
Summary: Partially hidden Markov models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where the hidden variables may be interpreted as ...
Søren Forchhammer, Jorma Rissanen
openaire   +2 more sources