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Heavy Tails and Copulas:Topics in Dependence Modelling in Economics and Finance

Author

Listed:
  • Rustam Ibragimov

    (Imperial College London, UK)

  • Artem Prokhorov

    (University of Sydney, Australia)

Abstract

"Overall, the book is highly technical, including full mathematical proofs of the results stated. Potential readers are post-graduate students or researchers in Quantitative Risk Management willing to have a manual with the state-of-the-art on portfolio diversification and risk aggregation with heavy tails, including the fundamental theorems as well as collateral (but most useful) results on majorization and copula theory."

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Rustam Ibragimov & Artem Prokhorov, 2017. "Heavy Tails and Copulas:Topics in Dependence Modelling in Economics and Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9644.
    • Handle: RePEc:wsi:wsbook:9644
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    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. Marat Ibragimov & Rustam Ibragimov, 2018. "Heavy tails and upper-tail inequality: The case of Russia," Empirical Economics, Springer, vol. 54(2), pages 823-837, March.
    2. Chen, Zhimin & Ibragimov, Rustam, 2019. "One country, two systems? The heavy-tailedness of Chinese A- and H- share markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 115-141.
    3. Damette, Olivier & Goutte, Stéphane, 2023. "Beyond climate and conflict relationships: New evidence from a Copula-based analysis on an historical perspective," Journal of Comparative Economics, Elsevier, vol. 51(1), pages 295-323.
    4. Marat Ibragimov & Rustam Ibragimov & Paul Kattuman & Jun Ma, 2018. "Income inequality and price elasticity of market demand: the case of crossing Lorenz curves," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(3), pages 729-750, May.
    5. Dietmar Pfeifer & Olena Ragulina, 2018. "Generating VaR Scenarios under Solvency II with Product Beta Distributions," Risks, MDPI, vol. 6(4), pages 1-15, October.
    6. Neveka M. Olmos & Emilio Gómez-Déniz & Osvaldo Venegas, 2022. "The Heavy-Tailed Gleser Model: Properties, Estimation, and Applications," Mathematics, MDPI, vol. 10(23), pages 1-16, December.
    7. Wang, Fangfang & Ma, Chunsheng, 2019. "ℓ1-symmetric vector random fields," Stochastic Processes and their Applications, Elsevier, vol. 129(7), pages 2466-2484.
    8. Pertaia, Giorgi & Prokhorov, Artem & Uryasev, Stan, 2022. "A new approach to credit ratings," Journal of Banking & Finance, Elsevier, vol. 140(C).
    9. Bikramjit Das & Vicky Fasen-Hartmann, 2023. "On heavy-tailed risks under Gaussian copula: the effects of marginal transformation," Papers 2304.05004, arXiv.org.
    10. León, Ángel & Ñíguez, Trino-Manuel, 2021. "The transformed Gram Charlier distribution: Parametric properties and financial risk applications," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 323-349.
    11. Brown, Donald & Ibragimov, Rustam, 2019. "Sign tests for dependent observations," Econometrics and Statistics, Elsevier, vol. 10(C), pages 1-8.
    12. Chanelle Duley & Prasanna Gai, 2023. "Macroeconomic tail risk, currency crises and the inter‐war gold standard," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(4), pages 1551-1582, November.

    Book Chapters

    The following chapters of this book are listed in IDEAS

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