Pooling Dynamic Conditional Correlation Models
نویسندگان
چکیده
منابع مشابه
Dynamic Conditional Correlation – a Simple Class of Multivariate Garch Models
Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be esti...
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Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the exibility of univariate GARCH models coupled with parsimonious parametric models for the c...
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Systemic risk arises from simultaneous movement or correlations between market segments; Thus, systemic risk occurs when there is a high correlation between the risks and crises of different market segments or institutions operating in the economy, or when the risks of different segments in a market segment or a country are related to other segments and other countries. This paper presents a me...
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This paper presents a method capable of estimating richly parametrized versions of the dynamic conditional correlation (DCC) model that go beyond the standard scalar case. The algorithm is based on the maximization of a Gaussian quasi-likelihood using a Bregman-proximal trust-region method to handle the various non-linear stationarity and positivity constraints that arise in this context. We co...
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ژورنال
عنوان ژورنال: Social Science Research Network
سال: 2021
ISSN: ['1556-5068']
DOI: https://doi.org/10.2139/ssrn.3929416