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The Structure and Degree of Dependence - A Quantile Regression Approach

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Abstract

The copula function defines the degree of dependence and the structure of dependence. This paper proposes an alternative framework to decompose the dependence using quantile regression. It is demonstrated that the methodology provides a detailed picture of dependence including asymmetric and non-linear relationships. In addition, changes in the degree or structure of dependence can be modelled and tested for each quantile of the distribution. The empirical part applies the framework to three different sets of financial time-series and demonstrates substantial differences in dependence patterns among asset classes and through time. The analysis of 54 global equity markets shows that detailed information about the structure of dependence is crucial to adequately assess the benefits of diversification in normal times and crisis times.

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File URL: http://www.finance.uts.edu.au/research/wpapers/wp170.pdf
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Bibliographic Info

Paper provided by Finance Discipline Group, UTS Business School, University of Technology, Sydney in its series Working Paper Series with number 170.

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Length: 42
Date of creation: 01 Aug 2012
Date of revision:
Publication status: Published as: Baur, D. G., 2013, "The Structure and Degree of Dependence - A Quantile Regression Approach", Journal of Banking and Finance, 37(3), 786-798.
Handle: RePEc:uts:wpaper:170

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Keywords: quantile regression; copula; dependence modelling; tail dependence; contagion; financial crises;

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Cited by:
  1. Walid Mensi & Shawkat Hammoudeh & Juan Carlos Reboredo & Duc Khuong Nguyen, 2014. "Do global factors impact BRICS stock markets? A quantile regression approach," Working Papers 2014-159, Department of Research, Ipag Business School.
  2. Elie I Bouri, 2013. "Correlation and Volatility of the MENA Equity Markets in Turbulent Periods, and Portfolio Implications," Economics Bulletin, AccessEcon, vol. 33(2), pages 1575-1593.
  3. Edgardo Cayon & Susan Thorp, 2013. "Financial Autarchy as Contagion Prevention: The Case of Colombian Pension Funds," Research Paper Series 323, Quantitative Finance Research Centre, University of Technology, Sydney.

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