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Risk classes for structured products: mathematical aspects and their implications on behavioral investors

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  • Ji Cao

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  • Marc Rieger

Abstract

The new regulation of the EU for financial products (UCITS IV) prescribes Value at Risk (VaR) as the benchmark for assessing the risk of structured products. We discuss the limitations of this approach and show that, in theory, the expected return of structured products is unbounded while the VaR requirement for the lowest risk class can still be satisfied. Real-life examples of large returns within the lowest risk class are then provided. The results demonstrate that the new regulation could lead to new seemingly safe products that hide large risks. Behavioral investors that choose products only based on their official risk classes and their expected returns will, therefore, invest into suboptimal products. To overcome these limitations, we suggest a new risk-return measure for financial products based on the martingale measure that could erase such loopholes. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Ji Cao & Marc Rieger, 2013. "Risk classes for structured products: mathematical aspects and their implications on behavioral investors," Annals of Finance, Springer, vol. 9(2), pages 167-183, May.
  • Handle: RePEc:kap:annfin:v:9:y:2013:i:2:p:167-183
    DOI: 10.1007/s10436-013-0223-8
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    References listed on IDEAS

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    1. Campbell, Rachel & Huisman, Ronald & Koedijk, Kees, 2001. "Optimal portfolio selection in a Value-at-Risk framework," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1789-1804, September.
    2. Marc Rieger, 2011. "Co-monotonicity of optimal investments and the design of structured financial products," Finance and Stochastics, Springer, vol. 15(1), pages 27-55, January.
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    7. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    8. Breuer, Wolfgang & Perst, Achim, 2007. "Retail banking and behavioral financial engineering: The case of structured products," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 827-844, March.
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    Citations

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    Cited by:

    1. Ji Cao, 2017. "How does the underlying affect the risk-return profiles of structured products?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 27-47, February.
    2. Martin Ewen, 2018. "Where is the Risk Reward? The Impact of Volatility-Based Fund Classification on Performance," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-20, August.
    3. H. Fink & S. Geissel & J. Sass & F. T. Seifried, 2019. "Implied risk aversion: an alternative rating system for retail structured products," Review of Derivatives Research, Springer, vol. 22(3), pages 357-387, October.

    More about this item

    Keywords

    Value at risk; Structured products; Risk measure; G28; G11; C61;

    JEL classification:

    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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