IDEAS home Printed from https://ideas.repec.org/p/gat/wpaper/1013.html
   My bibliography  Save this paper

Dépendance entre risques extrêmes : Application aux Hedge Funds

Author

Listed:
  • Ranoua Bouchouicha

    (Université de Lyon, Lyon, F-69003, France; CNRS, GATE Lyon St Etienne, UMR 5824, 93, chemin des Mouilles, Ecully, F-69130, France; ENS-LSH, Lyon, France)

Abstract

Compte tenu de l'importance de l'étude de la dépendance extrême, nous avons essayé de déterminer l'approche qui semble être la meilleure pour l'étude des risques extrêmes. Pour atteindre ce but, nous avons mené une étude du coefficient de dépendance de queue pour les trois approche : paramétriques, semi-paramétriques et non paramétriques. Dans l'étude empirique, nous estimons le coefficient de dépendance de queue dans le cadre de ces différentes méthodes, d'abord par une implémentation numérique, ensuite par l’étude de dépendance entre le Hedge Fund Credit Suisse / Tremont Market Neutral et le S & P500 afin d’évaluer le degré de dépendance entre ces deux actifs, qui sont connus pour être décorrélés. Il existe peu d'études qui ont travaillé sur la dépendance non linéaire entre les Hedge Funds et l'indice du marché. L'article de Denuit et Scaillet (2004) traite d'un cas général de la détection de la dépendance du quadrant positif (PQD) entre les HFR et CSFB / Tremont Market Neutral et l’indice S & P 500 index. Le résultat de ce papier est pertinent car on trouve que le niveau de dépendance au niveau des pertes avec l'indice de marché est moins important que celui au niveau des gains, alors que les Hedge Funds l'indice du marché sont généralement considérés comme décorrélés.

Suggested Citation

  • Ranoua Bouchouicha, 2010. "Dépendance entre risques extrêmes : Application aux Hedge Funds," Working Papers 1013, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    • Handle: RePEc:gat:wpaper:1013
    as

    Download full text from publisher

    File URL: ftp://ftp.gate.cnrs.fr/RePEc/2010/1013.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    2. P. Bortot & S. Coles & J. Tawn, 2000. "The multivariate Gaussian tail model: an application to oceanographic data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(1), pages 31-049.
    3. Rafael Schmidt & Ulrich Stadtmüller, 2006. "Non‐parametric Estimation of Tail Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 307-335, June.
    4. Karolyi, G Andrew & Stulz, Rene M, 1996. "Why Do Markets Move Together? An Investigation of U.S.-Japan Stock Return Comovements," Journal of Finance, American Finance Association, vol. 51(3), pages 951-986, July.
    5. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    6. Y. Malevergne & D. Sornette, . "How to account for extreme co-movements between individual stocks and the market," Journal of Risk, Journal of Risk.
    7. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    8. Yannick Malevergne & Didier Sornette, 2002. "Minimizing extremes," Post-Print hal-02312889, HAL.
    9. DENUIT, Michel & SAILLET, Olivier, 2001. "Nonparametric Tests for Positive Quadrant Dependence," LIDAM Discussion Papers IRES 2001009, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES), revised 01 Apr 2001.
    10. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
    11. Michel Denuit, 2004. "Nonparametric Tests for Positive Quadrant Dependence," Journal of Financial Econometrics, Oxford University Press, vol. 2(3), pages 422-450.
    12. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shegorika Rajwani & Dilip Kumar, 2016. "Asymmetric Dynamic Conditional Correlation Approach to Financial Contagion: A Study of Asian Markets," Global Business Review, International Management Institute, vol. 17(6), pages 1339-1356, December.
    2. Aguilar, Mike & Hill, Jonathan B., 2015. "Robust score and portmanteau tests of volatility spillover," Journal of Econometrics, Elsevier, vol. 184(1), pages 37-61.
    3. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    4. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    5. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.
    6. Maarten R C van Oordt & Chen Zhou, 2019. "Estimating Systematic Risk under Extremely Adverse Market Conditions," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 432-461.
    7. José Afonso Faias & Juan Arismendi Zambrano, 2022. "Equity Risk Premium Predictability from Cross-Sectoral Downturns [International asset allocation with regime shifts]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 808-842.
    8. Cotter, John & Longin, Francois, 2006. "Implied correlation from VaR," MPRA Paper 3506, University Library of Munich, Germany.
    9. Huang, Wei & Liu, Qianqiu & Ghon Rhee, S. & Wu, Feng, 2012. "Extreme downside risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1492-1502.
    10. Robert A. Jones & Christophe Pérignon, 2013. "Derivatives Clearing, Default Risk, and Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 373-400, June.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    12. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    13. Daniela Castro Camilo & Miguel de Carvalho & Jennifer Wadsworth, 2017. "Time-Varying Extreme Value Dependence with Application to Leading European Stock Markets," Papers 1709.01198, arXiv.org.
    14. Caicedo-Llano, Juliana & Dionysopoulos, Thomas, 2008. "Market integration: A risk-budgeting guide for pure alpha investors," Journal of Multinational Financial Management, Elsevier, vol. 18(4), pages 313-327, October.
    15. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306, Decembrie.
    16. Viviana Fernandez, 2006. "Extremal Dependence in European Capital Markets," Journal of Applied Economics, Taylor & Francis Journals, vol. 9(2), pages 275-293, November.
    17. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    18. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    19. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    20. Stefan Erdorf & Nicolas Heinrichs, 2011. "Co-movement of revenue: structural changes in the business cycle," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(4), pages 411-433, December.

    More about this item

    Keywords

    tail dependence; Copulas; parametric approach; non parametric approach; semiparametric approach;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G1 - Financial Economics - - General Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gat:wpaper:1013. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nelly Wirth The email address of this maintainer does not seem to be valid anymore. Please ask Nelly Wirth to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/gateefr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.