arXiv · 2404.00864
Convolution-t Distributions
Abstract
We introduce a new class of multivariate heavy-tailed distributions that are convolutions of heterogeneous multivariate t-distributions. Unlike commonly used heavy-tailed distributions, the multivariate convolution-t distributions embody cluster structures with flexible nonlinear dependencies and heterogeneous marginal distributions. Importantly, convolution-t distributions have simple density functions that facilitate estimation and likelihood-based inference. The characteristic features of convolution-t distributions are found to be important in an empirical analysis of realized volatility measures and help identify their underlying factor structure.
Explore related subjects
Keep this discovery
Peter Reinhard Hansen, Chen Tong. 2024-04-01. Convolution-t Distributions. https://arxiv.org/abs/2404.00864
Cite the original work for its findings. Save a collection to share your selection of sources.