Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T09:26:57.671Z Has data issue: false hasContentIssue false
  • English
  • Français

A simple isochore model evidencing regulation risk

Published online by Cambridge University Press:  27 February 2018

J. Lévy Véhel Open the ORCID record for J. Lévy Véhel [Opens in a new window]
J. Lévy Véhel*
Affiliation:
Anja team, INRIA Rennes, Université de Nantes, Laboratoire de mathé matiques Jean Leray, 2, Rue de la Houssiniere, 44000 Nantes, France
*
*Correspondence to: J. Lévy Véhel, Anja team, INRIA Rennes, Université de Nantes, Laboratoire de mathé matiques Jean Leray, 2, Rue de la Houssiniere, 44000 Nantes, France. E-mail: jacques.levy-vehel@inria.fr
Get access Rights & Permissions [Opens in a new window]

Abstract

In this note, we provide a simple example of regulation risk. The idea is that, in certain situations, the very prudential rules (or, rather, some of them) imposed by the regulator in the framework of the Basel II/III Accords or Solvency II directive are themselves the source of a systemic risk. The instance of regulation risk that we bring to light in this work can be summarised as follows: wrongly assuming that prices evolve in a continuous fashion when they may in fact display large negative jumps, and trying to minimise Value at Risk (VaR) under a constraint of minimal volume of activity leads in effect to behaviours that will maximise VaR. Although much stylised, our analysis highlights some pitfalls of model-based regulation.

Keywords

Regulation and systemic riskValue at riskHeavy-tailed processes
Type
Paper
Information
Annals of Actuarial Science , Volume 12 , Issue 2 , September 2018 , pp. 233 - 248
Copyright
© Institute and Faculty of Actuaries 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aggarwal, A., Beck, M.B., Cann, M., Ford, T., Georgescu, D., Morjaria, N., Smith, A., Taylor, Y., Tsanakas, A., Witts, L. & Ye, I. (2015). Model risk – daring to open up the black box. British Actuarial Journal, 21(2), 229–296.Google Scholar
Al-Darwish, A., Hafeman, M., Impavido, G., Kemp, M. & O’Malley, P. (2011). Possible unintended consequences of Basel III and Solvency II, IMF Working Paper No. 11/187.Google Scholar
Bank for International Settlements (BIS) Monetary and Economic Department (2014). Volatility stirs, markets unshaken, BIS Quarterly Review, September. Available online at the address https://www.bis.org/publ/qtrpdf/r_qt1409a.htm.Google Scholar
Bank of England. Procyclicality and structural trends in investment allocation by insurance companies and pension funds. A Discussion Paper by the Bank of England and the Procyclicality Working Group. Available online at the address http://www.bankofengland.co.uk/publications/Documents/news/2014/dp310714.pdf [accessed on 17-Feb-2018].Google Scholar
Basel Committee on Banking Supervision (2010). Basel III. A Global Regulatory Framework for More Resilient Banks and Banking Systems, Basel Committee on Banking Supervision. Bank for International Settlements: Basel. Revised version June 2011.Google Scholar
Bayraktar, E., Horst, U. & Sircar, R. (2006). A limit theorem for financial markets with inert investors. Mathematics of Operations Research, 31(4), 789–810.Google Scholar
Borio, C. (2014). Interview in Die Welt, 20 October 2014.Google Scholar
Carr, P., Geman, H., Madan, D. & Yor, M. (2002). The fine structure of asset returns: an empirical investigation. Journal of Business, 75, 305–332.Google Scholar
Carr, P. & Wu, L. (2002). The finite moment log stable process and option pricing. The Journal of Finance, Vol. LVIII(2), April 2003Google Scholar
Danelsson, J., Shin, H.S. & Zigrand, J.P. (2001). Asset price dynamics with value-at-risk constrained traders, London School of Economics Financial Markets Group Discussion Paper No. 394. Available online at the address http://www.lse.ac.uk/fmg/workingPapers/discussionPapers/fmg_pdfs/dp394.pdf [accessed on 17-Feb-2018].Google Scholar
Danelsson, J. & Zigrand, J.P. (2001). What happens when you regulate risk? Evidence from a simple equilibrium model, London School of Economics Financial Markets Group Discussion Paper No. 393. Available online at the address http://www.riskresearch.org/files/JZ-JD-01-8-11-997519763-10.pdf [accessed on 17-Feb-2018].Google Scholar
Danielsson, J., Embrechts, P., Goodhart, C., Keating, C., Muennich, F., Renault, O. & Shin, H.S. (2001). An academic response to Basel II, London School of Economics Financial Markets Group Special Paper No. 130. Available online at the address http://www.bis.org/bcbs/ca/fmg.pdf [accessed on 17-Feb-2018].Google Scholar
Danielsson, J., Shin, H. S & Zigrand, J.-P. (2013). Endogenous and systemic risk. In Haubrich J.G. & Lo A. W., (Eds.) NBER Book Quantifying Systemic Risk (pp. 73–94). University of Chicago Press, Chicago, IL.Google Scholar
El Mekeddem, H. & Lévy Véhel, J. (2013). Value at risk with tempered multistable motions, 30th International French Finance Association Conference, Lyon, France, May. Available online at the address https://hal.inria.fr/hal-00868634v1 [accessed on 17-Feb-2018].Google Scholar
Embrechts, P., McNeill, A. & Strautman, D. (1999). Risk Management: Value at Risk and Beyond (pp. 176–223). Cambridge University Press.Google Scholar
Fama, E.F. (1965). The behavior of stock market prices. Journal of Business, 38, 34–105.Google Scholar
International Actuarial Association (IAA) (2010). Note on the use of internal models for risk and capital management purposes by insurers, IAA Papers, November. Available online at the address http://www.actuaries.org/CTTEES_SOLV/Documents/Internal_Models_EN.pdf.Google Scholar
Khindanova, I., Rachev, S. & Schwartz, E. (2001). Stable modeling of value at risk. Mathematical and Computer Modelling, 34(9–11), 1223–1259.Google Scholar
Le Courtois, O. & Walter, C. (2014). Extreme Financial Risks and Asset allocation. Imperial College Press, London.Google Scholar
Lévy Véhel, J. & Walter, C. (2014). Regulation risk: is there a danger in reducing the volatility? 49th Actuarial Research Conference, Santa Barbara, CA, 13–16 July, 2014.Google Scholar
Mandelbrot, B. (1963). The variation of certain speculative prices. Journal of Business, 36, 394–419.Google Scholar
Mittnik, S., Rachev, S. & Schwartz, E. (2002). Value-at-risk and asset allocation with stable return distributions. Advances in Statistical Analysis, 86(1), 53–67.Google Scholar
Miyahara, Y. & Moriwaki, N. (2009). Option pricing based on geometric stable processes and minimal entropy martingale measures. In M. Kijima, M. Egami, K. Tanaka & Y. Muromachi (Eds.), Recent Advances in Financial Engineering, Proceedings of the 2008 Daiwa International Workshop on Financial Engineering (pp. 119–133), World Scientific, Tokyo.Google Scholar
Popovalina, I. & Ritchken, P. (1998). On bounding option prices in Paretian stable markets. The Journal of Derivatives , 5(4), Summer 1998.Google Scholar
Samorodnitsky, G. & Taqqu, M.S. (1994). Stable Non-Gaussian Random Processes. Chapman and Hall, London.Google Scholar
Sato, K.I. (1999). Lévy Processes and Infinitely Divisible Distributions . Cambridge University Press, Cambridge.Google Scholar
Sy, W. (2006). On the coherence of VAR risk measures for Levy stable distributions, 16 May. Available online at the address https://ssrn.com/abstract=2674989.Google Scholar
Zhu, L. & Li, H. (2010). Asymptotic analysis of tail conditional expectations. North American Actuarial Journal, 16(3), 350–363.Google Scholar