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On time-scaling of risk and the square–root–of–time rule

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  • Jean-Pierre Zigrand

    ()

  • Jon Danielsson

    ()

Abstract

Many financial applications, such as risk analysis and derivatives pricing, depend on time scaling of risk.� A common method for this purpose, though only correct when returns are iid normal, is the square root of time rule where an estimated quantile of a return distribution is scaled to a lower frequency by the square-root of the time horizon. The aim of this paper is to examine time scaling of risk when returns follow a jump diffusion process. It is argued that a jump diffusion is well-suited for the modeling of systemic risk, which is the raison d'etre of the Basel capital adequacy proposals. We demonstrate that the square root of time rule leads to a systematic underestimation of risk, whereby the degree of underestimation worsens with the time horizon,the jump intensity and the confidence level.� As a result,even if the square root of time rule has widespread applications in the Basel Accords, it fails to address the objective of the Accords.

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Bibliographic Info

Paper provided by Financial Markets Group in its series FMG Discussion Papers with number dp439.

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Date of creation: Mar 2003
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Handle: RePEc:fmg:fmgdps:dp439

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Cited by:
  1. 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.
  2. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel Smith, 2009. "Evaluating Value-at-Risk models via Quantile Regression," Economics Working Papers we094625, Universidad Carlos III, Departamento de Economía.
  3. Rossignolo, Adrian F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2012. "Value-at-Risk models and Basel capital charges," Journal of Financial Stability, Elsevier, vol. 8(4), pages 303-319.
  4. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, 01.
  5. Rodrigue Oeuvray & Pascal Junod, 2013. "On time scaling of semivariance in a jump-diffusion process," Papers 1311.1122, arXiv.org.
  6. Bakshi, Gurdip & Panayotov, George, 2010. "First-passage probability, jump models, and intra-horizon risk," Journal of Financial Economics, Elsevier, vol. 95(1), pages 20-40, January.
  7. Wang, Jying-Nan & Yeh, Jin-Huei & Cheng, Nick Ying-Pin, 2011. "How accurate is the square-root-of-time rule in scaling tail risk: A global study," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1158-1169, May.
  8. Pérignon, Christophe & Smith, Daniel R., 2010. "Diversification and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 55-66, January.
  9. 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.
  10. Amy S. K. Wong, 2006. "Basel II and the Risk Management of Basket Options with Time-Varying Correlations," International Journal of Central Banking, International Journal of Central Banking, vol. 2(4), December.
  11. Al Janabi, Mazin A. M., 2009. "Asset Market Liquidity Risk Management: A Generalized Theoretical Modeling Approach for Trading and Fund Management Portfolios," MPRA Paper 19498, University Library of Munich, Germany.
  12. Alfred Mbairadjim Moussa & Jules Sadefo Kamdem & Arnold F. Shapiro & Michel Terraza, 2012. "Capital asset pricing model with fuzzy returns and hypothesis testing," Working Papers 12-33, LAMETA, Universtiy of Montpellier, revised Sep 2012.
  13. Amadeo Alentorn & Sheri Markose, 2006. "Removing Maturity Effects of Implied Risk Neutral Densities and Related Statistics," Economics Discussion Papers 609, University of Essex, Department of Economics.

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