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International Equity Portfolio Risk Modeling: The Case of the NIG Model and Ordinary Copula Functions

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Abstract

Financial risk modeling and management are very important and challenging tasks for financial institutions’ quantitative units. Owing to the complex nature of portfolios, and given recent financial market developments, contemporary research is focused on tail modeling and/or dependency modeling. The main objective of this paper is to examine the potential contribution of Lévy-based subordinated models coupled by ordinary elliptical copula functions to the estimation of the distribution pattern of international equity portfolios. The authors observe that the subordinated NIG model coupled with the Student copula function, and in particular its combined estimation version, allows them to get very good estimates of portfolio risk measures.

Suggested Citation

  • Ales Kresta & Tomas Tichy, 2012. "International Equity Portfolio Risk Modeling: The Case of the NIG Model and Ordinary Copula Functions," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(2), pages 141-161, May.
  • Handle: RePEc:fau:fauart:v:62:y:2012:i:2:p:141-161
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    1. Benoit Mandelbrot & Howard M. Taylor, 1967. "On the Distribution of Stock Price Differences," Operations Research, INFORMS, vol. 15(6), pages 1057-1062, December.
    2. Peter Christoffersen, 2004. "Backtesting Value-at-Risk: A Duration-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 84-108.
    3. Madan, Dilip B & Seneta, Eugene, 1990. "The Variance Gamma (V.G.) Model for Share Market Returns," The Journal of Business, University of Chicago Press, vol. 63(4), pages 511-524, October.
    4. Katja Ignatieva & Eckhard Platen, 2010. "Modelling Co-movements and Tail Dependency in the International Stock Market via Copulae," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 17(3), pages 261-302, September.
    5. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer;Western Finance Association, vol. 12(2), pages 201-242, October.
    6. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    7. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value‐at‐Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, June.
    8. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
    9. Huang, Jen-Jsung & Lee, Kuo-Jung & Liang, Hueimei & Lin, Wei-Fu, 2009. "Estimating value at risk of portfolio by conditional copula-GARCH method," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 315-324, December.
    10. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
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    Cited by:

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    2. Monika Brzezińska & Katarzyna Guhn, 2013. "Planning of sales on the example of companies in the paper industry and wholesale of chemical products," Working Papers hal-00812840, HAL.
    3. Dejan Zivkov & Slavica Manic & Jasmina Duraskovic & Jelena Kovacevic, 2019. "Bidirectional Nexus between Inflation and Inflation Uncertainty in the Asian Emerging Markets – The GARCH-in-Mean Approach," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(6), pages 580-599, December.
    4. Dejan Zivkov & Marina Gajic-Glamoclija & Jelena Kovacevic & Sanja Loncar, 2020. "Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(5), pages 461-486, November.
    5. Katarzyna Guhn, 2013. "Krotkoterminowe planowanie finansowe na przykladzie przedsiebiorstwa z branzy sprzedaz hurtowa wyrobow chemicznych," Working Papers hal-00816775, HAL.

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    More about this item

    Keywords

    market risk; backtesting; subordinated Lévy model; VaR;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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