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Implied risk aversion: an alternative rating system for retail structured products

Author

Listed:
  • H. Fink

    (Munich University of Applied Sciences)

  • S. Geissel

    (HSBC Germany)

  • J. Sass

    (University of Kaiserslautern)

  • F. T. Seifried

    (University of Trier)

Abstract

This article proposes implied risk aversion as a rating methodology for retail structured products. Implied risk aversion is based on optimal expected utility risk measures as introduced by Geissel et al. (Stat Risk Model 35(1–2):73–87, 2017) and, in contrast to standard V@R-based ratings, takes into account both the upside potential and the downside risks of such products. In addition, implied risk aversion is easily interpreted in terms of an individual investor’s risk aversion: a product is attractive for an investor if his individual relative risk aversion is smaller than the product’s implied risk aversion. We illustrate our approach in a case study with more than 15,000 short-term warrants on DAX that highlights some differences between our rating system and the traditional V@R-based approach.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:revdev:v:22:y:2019:i:3:d:10.1007_s11147-018-9151-0
    DOI: 10.1007/s11147-018-9151-0
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    3. S. Geissel & H. Graf & J. Herbinger & F. T. Seifried, 2022. "Portfolio optimization with optimal expected utility risk measures," Annals of Operations Research, Springer, vol. 309(1), pages 59-77, February.

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    More about this item

    Keywords

    Structured products; Risk measures; Optimal expected utility; Implied risk aversion;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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