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Copulas and Tail Dependence in Finance

In: HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING

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  • Wing-Choong Lai
  • Kim-Leng Goh

Abstract

This chapter discusses the copula methods for application in finance. It provides an overview of the concept of copula, and the underlying statistical theories as well as theorems involved. The focus is on two copula families, namely, the elliptical and Archimedean copulas. The Gaussian and Student’s t copulas in the family of elliptical copulas which have symmetrical tails in their distributions are explained. The Clayton and Gumbel copulas in the family of Archimedean copulas whose distributions are asymmetrical are also described. Elaborations are given on tail dependence and the associated measures for these copulas. The estimation process is illustrated using an application of the methods on the returns of two exchange series.

Suggested Citation

  • Wing-Choong Lai & Kim-Leng Goh, 2020. "Copulas and Tail Dependence in Finance," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 73, pages 2499-2524, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789811202391_0073
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    More about this item

    Keywords

    Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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