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20242026
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econ.EM2026

Split-Session Cluster GARCH for Overnight and Intraday Returns: The Role of Tail Heterogeneity

Xinxian Chen, Peter Reinhard Hansen, Chen Tong

We propose the Split-Session Cluster GARCH model for heavy-tailed multivariate dependence among asset returns decomposed into overnight and intraday components. The model uses conv…

econ.EM2026

Moments by Integrating the Moment-Generating Function

Peter Reinhard Hansen, Chen Tong

We introduce a general integral framework for computing fractional, complex, absolute, and logarithmic moments from the moment-generating function (MGF) under explicit regularity c…

econ.EM2026

Exact Likelihood Inference and Robust Filtering for Gauss-Cauchy Convolution Models

Peter Reinhard Hansen, Chen Tong

The convolution of a Gaussian and a Cauchy distribution, known as the Voigt distribution, is widely used in spectroscopy and provides a natural framework for modeling heavy-tailed…

econ.EM2026

Principled Identification of Structural Dynamic Models

Neville Francis, Peter Reinhard Hansen, Chen Tong

We take a new perspective on identification in structural dynamic models: rather than imposing restrictions alone, we optimize an objective. While definitive structural identificat…

econ.EM2025

Dynamic Factor Correlation Model

Chen Tong, Peter Reinhard Hansen

We introduce a new dynamic factor correlation model with a novel variation-free parametrization of factor loadings. The model is applicable to high dimensions and can accommodate t…

econ.EM2024

Cluster GARCH

Chen Tong, Peter Reinhard Hansen, Ilya Archakov

We introduce a novel multivariate GARCH model with flexible convolution-t distributions that is applicable in high-dimensional systems. The model is called Cluster GARCH because it…