IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1009.3638.html
   My bibliography  Save this paper

Scaling portfolio volatility and calculating risk contributions in the presence of serial cross-correlations

Author

Listed:
  • Nikolaus Rab
  • Richard Warnung

Abstract

In practice daily volatility of portfolio returns is transformed to longer holding periods by multiplying by the square-root of time which assumes that returns are not serially correlated. Under this assumption this procedure of scaling can also be applied to contributions to volatility of the assets in the portfolio. Close prices are often used to calculate the profit and loss of a portfolio. Trading at exchanges located in distant time zones this can lead to significant serial cross-correlations of the closing-time returns of the assets in the portfolio. These serial correlations cause the square-root-of-time rule to fail. Moreover volatility contributions in this setting turn out to be misleading due to non-synchronous correlations. We address this issue and provide alternative procedures for scaling volatility and calculating risk contributions for arbitrary holding periods.

Suggested Citation

  • Nikolaus Rab & Richard Warnung, 2010. "Scaling portfolio volatility and calculating risk contributions in the presence of serial cross-correlations," Papers 1009.3638, arXiv.org, revised Nov 2011.
    • Handle: RePEc:arx:papers:1009.3638
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1009.3638
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Danielsson, Jon & Zigrand, Jean-Pierre, 2006. "On time-scaling of risk and the square-root-of-time rule," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2701-2713, October.
    2. Dirk Tasche, 2007. "Capital Allocation to Business Units and Sub-Portfolios: the Euler Principle," Papers 0708.2542, arXiv.org, revised Jun 2008.
    3. repec:dau:papers:123456789/4688 is not listed on IDEAS
    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. George Tzagkarakis & Frantz Maurer, 2020. "An energy-based measure for long-run horizon risk quantification," Annals of Operations Research, Springer, vol. 289(2), pages 363-390, June.
    2. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.
    3. repec:hal:journl:hal-00921283 is not listed on IDEAS
    4. Said Khalil, 2022. "Expectile-based capital allocation," Working Papers hal-03816525, HAL.
    5. Bennani, T. & Després, M. & Dujardin, M. & Duprey, T. & Kelber, A., 2014. "Macroprudential framework:key questions applied to the French case," Occasional papers 9, Banque de France.
    6. Toumi, Kaouther & Viviani, Jean-Laurent & Chayeh, Zeinab, 2019. "Measurement of the displaced commercial risk in Islamic Banks," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 18-31.
    7. Ivan Granito & Paolo De Angelis, 2015. "Capital allocation and risk appetite under Solvency II framework," Papers 1511.02934, arXiv.org.
    8. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    9. Véronique Maume-Deschamps & Didier Rullière & Khalil Said, 2014. "On capital allocation by minimizing multivariate risk indicators," Working Papers hal-01082559, HAL.
    10. Luca Spadafora & Marco Dubrovich & Marcello Terraneo, 2014. "Value-at-Risk time scaling for long-term risk estimation," Papers 1408.2462, arXiv.org.
    11. Stavros Degiannakis & Apostolos Kiohos, 2014. "Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 216-232, March.
    12. Adrián F. Rossignolo & Víctor A. Álvarez, 2015. "Has the Basel Committee Got it Right? Evidence from Commodity Positions in Turmoil," Remef - The Mexican Journal of Economics and Finance, Instituto Mexicano de Ejecutivos de Finanzas. Remef, March.
    13. Rodrigue Oeuvray & Pascal Junod, 2013. "On time scaling of semivariance in a jump-diffusion process," Papers 1311.1122, arXiv.org.
    14. Koike, Takaaki & Saporito, Yuri & Targino, Rodrigo, 2022. "Avoiding zero probability events when computing Value at Risk contributions," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 173-192.
    15. Kao, Lie-Jane, 2015. "A portfolio-invariant capital allocation scheme penalizing concentration risk," Economic Modelling, Elsevier, vol. 51(C), pages 560-570.
    16. Jianping Li & Lu Wei & Cheng-Few Lee & Xiaoqian Zhu & Dengsheng Wu, 2018. "Financial statements based bank risk aggregation," Review of Quantitative Finance and Accounting, Springer, vol. 50(3), pages 673-694, April.
    17. Yinhong Yao & Jianping Li, 2022. "Operational risk assessment of third-party payment platforms: a case study of China," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-20, December.
    18. Fritzsch, Simon & Timphus, Maike & Weiß, Gregor, 2024. "Marginals versus copulas: Which account for more model risk in multivariate risk forecasting?," Journal of Banking & Finance, Elsevier, vol. 158(C).
    19. Dora Balog, 2011. "Capital allocation in financial institutions: the Euler method," CERS-IE WORKING PAPERS 1126, Institute of Economics, Centre for Economic and Regional Studies.
    20. Shan Lu, 2019. "Testing the Predictive Ability of Corridor Implied Volatility Under GARCH Models," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(2), pages 129-168, June.
    21. Mikhail Voropaev, 2011. "KISS approach to credit portfolio modeling," Papers 1107.2164, arXiv.org.

    More about this item

    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:arx:papers:1009.3638. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.