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International Econometric Conference of Vietnam

ECONVN 2019: Beyond Traditional Probabilistic Methods in Economics pp 818–827Cite as

Bayesian Approach for Mixture Copula Model

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 809))

Abstract

This paper aims to use the Bayesian estimation as an alternative method for formulating and estimating mixed copula models. This method has claimed to be more efficient than the conventional maximum likelihood estimator as it can deal with the high dimension copula and large parameter estimates under limited sample. In this study, we present various mixed copula functions constructed from both Elliptical and Archimedean copulas. We employ a simulation study to investigate the performance of this estimator for comparison with the maximum likelihood estimator. The results show that the Bayesian estimation is considerably more accurate than maximum likelihood estimator in various scenarios. Finally, we extend the Bayesian mixed copula to the real data and show that our approach perform well in this real data analysis.

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Acknowledgements

The authors are grateful to Puay Ungphakorn Centre of Excellence in Econometrics, Faculty of Economics, Chiang Mai University for the financial support.

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Authors and Affiliations

  1. Center of Excellence in Econometrics, Faculty of Economics, Chiang Mai University, Chiang Mai, 50200, Thailand

    Sukrit Thongkairat, Woraphon Yamaka & Songsak Sriboonchitta

  2. International College of Digital Innovation, Chiang Mai University, Chiang Mai, 50200, Thailand

    Sukrit Thongkairat

Authors
  1. Sukrit Thongkairat
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  2. Woraphon Yamaka
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  3. Songsak Sriboonchitta
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Corresponding author

Correspondence to Sukrit Thongkairat .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

  3. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Duc Trung

  4. TTC Group, Ho Chi Minh City, Vietnam

    Dang Van Thanh

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Thongkairat, S., Yamaka, W., Sriboonchitta, S. (2019). Bayesian Approach for Mixture Copula Model. In: Kreinovich, V., Thach, N., Trung, N., Van Thanh, D. (eds) Beyond Traditional Probabilistic Methods in Economics. ECONVN 2019. Studies in Computational Intelligence, vol 809. Springer, Cham. https://doi.org/10.1007/978-3-030-04200-4_58

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