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Convolution-t Distributions

Peter Reinhard Hansen, Chen Tong

arXiv 1 Apr 2024 · Econometrics · 1 citations (OpenAlex)

arXiv:2404.00864 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

65
references
76
in-text mentions
65
distinct cited
4
self-citations
16,994
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Patil, V. H (1965) Approximation to the Behrens-Fisher distributions0.73732100%
2Nadarajah, S. and Dey, D. K (2005) Convolutions of the T distribution0.58531100%
3Kawata, T (1972) Fourier analysis in probability theory0.5112250%
4Hurst, S (1995) The characteristic function of the Student t distribution0.51121100%
5Kendall, D. G (1938) The effect of radiation damping and doppler broadening on the atomic absorption coefficient0.51121100%
6Nason, G. P (2006) On the sum of t and Gaussian random variables0.51121100%
7Andersen, T. G., Bollerslev, T., and Diebold, F. X (2007) Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility0.40511100%
8Archakov, I. and Hansen, P. R (2023) A canonical representation of block matrices with applications to covariance and correlation matrices self0.40511100%
9Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., and Shephard, N (2011) Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and n… self0.40511100%
10Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., and Shephard, N (2008) Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise self0.40511100%

Showing the top 10 of 65 scored citations.