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Explicit-Duration Markov Switching Models [PDF]
Foundations and Trends® in Machine Learning, 2014 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.
openaire +2 more sources
Regime‐Dependent Nowcasting of the Austrian Economy
Journal of Forecasting, EarlyView.ABSTRACT We nowcast and forecast economic activity in Austria, namely, real gross domestic product (GDP), consumption, and investment, which are available at a quarterly frequency, using a preselected number of monthly indicators based on a combination of statistical procedures.
Jaroslava Hlouskova, Ines Fortin
wiley +1 more source
Estimating the risk of SARS-CoV-2 deaths using a Markov switching-volatility model combined with heavy-tailed distributions for South Africa. [PDF]
BMC Public Health, 2022 Mthethwa N, Chifurira R, Chinhamu K.
europepmc +2 more sources
Науковий вісник Ужгородського університету. Серія: Математика і інформатика, 2017 Sufficient conditions equivalent concepts of stochastic stability and exponential stability in the mean square for stochastic dynamic systems random structure with Markov switching are obtained.
T. O. Лукашів, І. В. Малик
doaj +1 more source
Inference and forecasting phase shift regime of COVID-19 sub-lineages with a Markov-switching model. [PDF]
Microbiol Spectr, 2023 Noh E, Hong J, Yoo J, Jung J.
europepmc +1 more source
Testing the Unbiased Forward Exchange Rate Hypothesis Using a Markov Switching Model and Instrumental Variables [PDF]
, 2003 This paper develops a model for the forward and spot exchange rate which allows for the presence of a Markov switching risk premium in the forward market and considers the issue of testing for the unbiased forward exchange rate (UFER) hypothesis. Using
Psaradakis, Z, Sola, M, Spagnolo, F
core +1 more source
Using DSGE and Machine Learning to Forecast Public Debt for France
Journal of Forecasting, EarlyView.ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source
Synchronization in Cycles of China and India During Recent Crises: A Markov Switching Analysis. [PDF]
J Quant Econ, 2023 Dua P, Tuteja D.
europepmc +1 more source
Markov-Switching Model Selection Using Kullback-Leibler Divergence [PDF]
In Markov-switching regression models, we use Kullback-Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously.
Naik, Prasad A. +2 more
core +1 more source
Journal of Forecasting, EarlyView.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 +3 more
wiley +1 more source