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Value-at-risk capital requirement regulation, risk taking and asset allocation: a mean-variance analysis

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  • Guy Kaplanski
  • Haim Levy

Abstract

In this study, the mean-variance framework is employed to analyze the impact of the Basel value-at-risk (VaR) market risk regulation on the institution's optimal investment policy, the stockholders' welfare, as well as the tendency of the institution to change the risk profile of the held portfolio. It is shown that with the VaR regulation, the institution faces a new regulated capital market line, which induces resource allocation distortion in the economy. Surprisingly, only when a riskless asset is available does VaR regulation induce the institution to reduce risk. Otherwise, the regulation may induce higher risk, accompanied by asset allocation distortion. On the positive side, the regulation implies an upper bound on the risk the institution takes and it never induces the firm to select an inefficient portfolio. Moreover, when the riskless asset is available, tightening the regulation always increases the amount of maintained eligible capital and decreases risk.

Suggested Citation

  • Guy Kaplanski & Haim Levy, 2015. "Value-at-risk capital requirement regulation, risk taking and asset allocation: a mean-variance analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 21(3), pages 215-241, February.
    • Handle: RePEc:taf:eurjfi:v:21:y:2015:i:3:p:215-241
    DOI: 10.1080/1351847X.2013.802249
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    Citations

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    Cited by:

    1. Ana-Maria Gavril, 2009. "Exchange Rate Risk: Heads or Tails," Advances in Economic and Financial Research - DOFIN Working Paper Series 35, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    2. Lawrence Haar & Andros Gregoriou, 2023. "Regulation and De-Risking: Theoretical and Empirical Insights," Risks, MDPI, vol. 11(6), pages 1-23, June.
    3. Landsman, Zinoviy & Makov, Udi & Shushi, Tomer, 2016. "Tail conditional moments for elliptical and log-elliptical distributions," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 179-188.
    4. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    5. Morten Balling & Ernest Gnan, 2013. "The development of financial markets and financial theory: 50 years of interaction," SUERF 50th Anniversary Volume Chapters, in: Morten Balling & Ernest Gnan (ed.), 50 Years of Money and Finance: Lessons and Challenges, chapter 5, pages 157-194, SUERF - The European Money and Finance Forum.
    6. Iglesias, Emma M., 2015. "Value at Risk and expected shortfall of firms in the main European Union stock market indexes: A detailed analysis by economic sectors and geographical situation," Economic Modelling, Elsevier, vol. 50(C), pages 1-8.
    7. Dawen Yan & Xiaohui Zhang & Mingzheng Wang, 2021. "A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations," Annals of Operations Research, Springer, vol. 299(1), pages 659-710, April.
    8. Shushi, Tomer, 2019. "The Minkowski length of a spherical random vector," Statistics & Probability Letters, Elsevier, vol. 153(C), pages 104-107.

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