Skip to main content
Log in

Stochastic dominance of portfolio insurance strategies

OBPI versus CPPI

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

The purpose of this article is to analyze and compare two standard portfolio insurance methods: Option-based Portfolio Insurance (OBPI) and Constant Proportion Portfolio Insurance (CPPI). Various stochastic dominance criteria up to third order are considered. We derive parameter conditions implying the second- and third-order stochastic dominance of the CPPI strategy. In particular, restrictions on the CPPI multiplier resulting from the spread between the implied volatility and the empirical volatility are analyzed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Arrow, K. J. (1965). Aspects of the theory of risk-bearing. Helsinki: Yrjö Hahnsson Foundation.

    Google Scholar 

  • Bertrand, P., & Prigent, J. L. (2002). Portfolio insurance: the extreme value to the CPPI method. Finance, 23, 69–86.

    Google Scholar 

  • Bertrand, P., & Prigent, J. L. (2005). Portfolio insurance strategies: OBPI versus CPPI. Finance, 26, 5–32.

    Google Scholar 

  • Black, F., & Jones, R. (1987). Simplifying portfolio insurance. Journal of Portfolio Management, 13, 48–51.

    Article  Google Scholar 

  • Black, F., & Perold, A. (1992). Theory of constant portfolio insurance. Journal of Economic Dynamics and Control, 186, 402–426.

    Google Scholar 

  • Black, F., & Rouhani, R. (1989). Constant proportion portfolio insurance and the synthetic put option: a comparison. In F. J. Fabozzi (Ed.), Institutional investor focus on investment management (pp. 695–708). Ballinger: Cambridge.

    Google Scholar 

  • Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81, 637–659.

    Article  Google Scholar 

  • Bookstaber, R., & Langsam, J. A. (2000). Portfolio insurance trading rules. Journal of Futures Markets, 20(1), 41–57.

    Article  Google Scholar 

  • Elton, E. J., Gruber, M. J., (2006). Modern portfolio theory and investment analysis (7th edn.). New York: Wiley.

    Google Scholar 

  • Fahrmeir (2003). Statistik—der Weg zur Datenanalyse. Heidelberg: Springer.

    Google Scholar 

  • Karlin, S., & Novikov, A. (1963). Generalized convex inequalities. Pacific Journal of Mathematics, 13, 1251–1279.

    Google Scholar 

  • Leland, H. E., & Rubinstein, M. (1988). The evolution of portfolio insurance. In Dynamic hedging: a guide to portfolio insurance. New York: Wiley.

    Google Scholar 

  • Mosler, K. C. (1982). Entscheidungsregeln bei Risiko—Multivariate stochastische Dominanz. Heidelberg: Springer.

    Google Scholar 

  • Perold, A. (1986). A constant proportion portfolio insurance. Unpublished manuscript, Harvard Business School.

  • Perold, A., & Sharpe, W. (1988). Dynamic strategies for asset allocation. Financial Analyst Journal, 1988, 16–27 January–February.

    Article  Google Scholar 

  • Shreve, S. E. (2004). Stochastic calculus for finance II—continuous-time models. New York: Springer.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Julia Kraus.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zagst, R., Kraus, J. Stochastic dominance of portfolio insurance strategies. Ann Oper Res 185, 75–103 (2011). https://doi.org/10.1007/s10479-009-0549-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-009-0549-9

Keywords

Navigation