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Modeling the Dependency Structure of Stock Index Returns using a Copula Function Approach

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  • Necula, Ciprian

    ()
    (DOFIN, Academy of Economic Studies, Bucharest; Center for Advanced Research in Finance and Banking (CARFIB); Centrul de Analiza si Prognoza Economico-Financiara (CAPEF))

Abstract

In the present study we assess the dependency structure between stock indexes by econometrically estimating the empirical copula function and the parameters of various parametric copula functions. The main finding is that the t-copula and the Gumbel-Clayton mixture copula are the most appropriate copula functions to capture the dependency structure of two financial return series. With the dependency structure given by the estimated copula functions we quantify the efficient portfolio frontier using as a risk measure CVaR (Conditional VaR) computed by Monte Carlo simulation. We find that in the case of using normal distributions for modeling individual returns the market risk is underestimated no mater what copula function is employed to capture the dependency structure.

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Bibliographic Info

Article provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.

Volume (Year): (2010)
Issue (Month): 3 (September)
Pages: 93-106

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Handle: RePEc:rjr:romjef:v::y:2010:i:3:p:93-106

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Related research

Keywords: copula functions; copula mixtures; the efficient portfolio frontier; Conditional VAR; Monte Carlo simulation;

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References

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  1. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
  2. Necula, Ciprian, 2009. "Modeling Heavy-Tailed Stock Index Returns Using the Generalized Hyperbolic Distribution," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(2), pages 118-131, June.
  3. Jean-David FERMANIAN & Olivier SCAILLET, 2003. "Nonparametric Estimation of Copulas for Time Series," FAME Research Paper Series rp57, International Center for Financial Asset Management and Engineering.
  4. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
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Cited by:
  1. Dajcman, Silvio & Festic, Mejra, 2012. "The Interdependence of the Stock Markets of Slovenia, The Czech Republic and Hungary with Some Developed European Stock Markets – The Effects of Joining the European Union and the Global Financial C," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 163-180, December.

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