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, 2016 The phenomenon of growing capital market linkages is a significant exogenous factor affecting the effectiveness of national economic policies and risk management processes in enterprises. As a result the identification of interdependencies among capital markets is important both from the macro and microeconomic perspective. In this context the main aim
Zineker, Marek +4 more
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Modeling structure of inflation in Türkiye: DCC-GARCH and Markov switching model
Journal of Financial Economic PolicyPurpose Recent surges in inflation have posed significant challenges for Türkiye, with the annualinflation rate culminating at 83.45% by the close of 2022. The purpose of the study is to take a closer look at the details behind the rising inflation trend in Türkiye.
Evan Lau +2 more
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Linear time-varying regression with Copula–DCC–GARCH models for volatility
Economics Letters, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, Jong-Min, Jung, Hojin
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Comparison of BEKK GARCH and DCC GARCH Models: An Empirical Study
2010Modeling volatility and co-volatility of a few zero-coupon bonds is a fundamental element in the field of fix-income risk evaluation. Multivariate GARCH model (MGARCH), an extension of the well-known univariate GARCH, is one of the most useful tools in modeling the co-movement of multivariate time series with time-varying covariance matrix. Grounded on
Yiyu Huang, Wenjing Su, Xiang Li 0033
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Variance Minimization Hedging Analysis Based on a Time-Varying Markovian DCC-GARCH Model
IEEE Transactions on Automation Science and Engineering, 2020Considering time-varying transition probability (TVTP), this article combines Markov regime switching with a dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model to construct a new hedging model and study a state-dependent minimum variance hedging ratio.
Jia Wang 0047 +5 more
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Apple, Microsoft, Amazon and Google - A Correlation Analysis: Evidence from a DCC-GARCH Model
SSRN Electronic Journal, 2020In this paper, we examine time-varying correlations among stock returns of Apple, Microsoft, Amazon and Google. Employing a multivariate DCC-GARCH model, we find that there are strong linkages among these four assets. Starting from lower levels, correlation values for most asset pairs exhibit a stable ascending movement in recent upward trended markets
Christoph Koser, Juergen Klaus
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Neuroscience Research, 2021
We suggest a time-varying partial correlation as a statistical measure of dynamic functional connectivity (dFC) in the human brain. Traditional statistical models often assume specific distributions on the measured data such as the Gaussian distribution, which prohibits their application to neuroimaging data analysis.
Namgil, Lee, Jong-Min, Kim
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We suggest a time-varying partial correlation as a statistical measure of dynamic functional connectivity (dFC) in the human brain. Traditional statistical models often assume specific distributions on the measured data such as the Gaussian distribution, which prohibits their application to neuroimaging data analysis.
Namgil, Lee, Jong-Min, Kim
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Directional time-varying partial correlation with the Gaussian copula–DCC–GARCH model
Applied Economics, 2018This article suggests a directional time-varying partial correlation based on the dynamic conditional correlation (DCC) method. A recent study proposed the copula DCC based on the vine structure.
Jong-Min Kim, Hojin Jung
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The more contagion effect on emerging markets: The evidence of DCC-GARCH model
Economic Modelling, 2012Abstract The paper aims to test the existence of financial contagion between foreign exchange markets of several emerging and developed countries during the U.S. subprime crisis. As a result of DCC-GARCH analysis, we find the evidence of contagion during U.S. subprime crisis for most of the developed and emerging countries.
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