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Pooling Dynamic Conditional Correlation Models [PDF]
SSRN Electronic Journal, 2021 The Dynamic Conditional Correlation (DCC) model by Engle (2002) has become an extremely popular tool for modeling the time-varying dependence of asset returns. However, applications to large cross-sections have been found to be problematic, due to the curse of dimensionality. We propose a novel DCC model with Conditional LInear Pooling (CLIP-DCC) which
van Os, Bram, van Dijk, Dick
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The dynamic relationship between BTC with BIST and NASDAQ indices
Financial Internet Quarterly, 2023 The significance of digital investment has grown substantially, enabled by advancing technology, which provides digital monitoring of investment instruments. Consequently, analyzing these instruments has become imperative.
Ulu Cagri
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Analytical Gradients of Dynamic Conditional Correlation Models [PDF]
Journal of Risk and Financial Management, 2020 We provide the analytical gradient of the full model likelihood for the Dynamic Conditional Correlation (DCC) specification by Engle (2002), the generalised version by Cappiello et al. (2006), and of the cDCC model by Aielli(2013). We discuss how the gradient might be further extended by introducing elements related to the conditional variance ...
Massimiliano Caporin +2 more
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Energy Reports, 2021 The planning of the park-level integrated energy system (PIES) is a long-term process, it faces risk caused by the volatility of energy prices including the natural gas price (NGP) and the electricity price (EP). The uncertainties of them are complex and
Yan Cao +5 more
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Projected Dynamic Conditional Correlations
International Journal of Forecasting, 2020 We propose a novel specification of the Dynamic Conditional Correlation (DCC) model based on an alternative normalization of the pseudo-correlation matrix called Projected DCC (Pro-DCC). Our modification consists in projecting, rather than rescaling, the pseudo-correlation matrix onto the set of correlation matrices in order to obtain a well defined ...
Llorens-Terrazas J., Brownlees C.
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The Co-movement between Output and Prices: Evidence from Iran [PDF]
International Journal of Business and Development Studies, 2015 This paper employs a multivariate dynamic conditional correlation GARCH model, which is developed by Engle (2001, 2002), to detect the timing and nature of changes in the comovement between Iranian output and prices for the periods after Iran–Iraq war ...
Esmaeil Pishbahar +2 more
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Frontiers in Energy Research, 2023 With a high proportion of photovoltaic (PV) connected to the active distribution network (ADN), the correlation and uncertainty of the PV output will significantly affect the grid dispatching operation.
Xin Ma, Han Wu, Yue Yuan
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Estimation of Dynamic Bivariate Correlation Using a Weighted Graph Algorithm
Entropy, 2020 Dynamic correlation is the correlation between two time series across time. Two approaches that currently exist in neuroscience literature for dynamic correlation estimation are the sliding window method and dynamic conditional correlation. In this paper,
Majnu John +5 more
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Cogent Economics & Finance, 2023 The present study conducts a dynamic conditional cross-correlation and time–frequency correlation analyses between cryptocurrency and equity markets in both advanced and emerging economies. The purpose of the study is twofold.
Olivier Niyitegeka, Sheunesu Zhou
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Dynamic Conditional Correlations for Asymmetric Processes [PDF]
JOURNAL OF THE JAPAN STATISTICAL SOCIETY, 2009 The paper develops two Dynamic Conditional Correlation (DCC) models, namely the Wishart DCC (wDCC) model. The paper applies the wDCC approach to the exponential GARCH (EGARCH) and GJR models to propose asymmetric DCC models. We use the standardized multivariate t-distribution to accommodate heavy-tailed errors.
Asai, Manabu, McAleer, Michael
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