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Best portfolio insurance for long-term investment strategies in realistic conditions

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  • Pézier, Jacques
  • Scheller, Johanna

Abstract

Constant proportion portfolio insurance (CPPI) strategies implemented in continuous time on asset prices following geometric Brownian processes are expected utility maximising for investors with HARA utilities. But, in reality, these strategies are implemented in discrete time and asset prices might jump. We show that under these more realistic circumstances, optimal CPPI strategies are still superior to optimal option based portfolio insurance (OBPI) strategies. The effects of discrete replication and jumps on optimal strategy parameters and certainty equivalent returns (CER) are examined by simulation and turn out to be minor in typical circumstances. Hence the much discussed gap risks are unimportant for investors in both portfolio insurance strategies and comparable for insurers of the gap risks.

Suggested Citation

  • Pézier, Jacques & Scheller, Johanna, 2013. "Best portfolio insurance for long-term investment strategies in realistic conditions," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 263-274.
    • Handle: RePEc:eee:insuma:v:52:y:2013:i:2:p:263-274
    DOI: 10.1016/j.insmatheco.2013.01.001
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    References listed on IDEAS

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    Cited by:

    1. Ariful Hoque & Robin Kämmer & Frieder Meyer-Bullerdiek, 2018. "Portfolio insurance strategies in a low interest rate environment: A simulation based study," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 7(3), pages 1-2.
    2. Zhang, Tao & Zhou, Hongfeng & Li, Larry & Gu, Feng, 2015. "Optimal rebalance rules for the constant proportion portfolio insurance strategy – Evidence from China," Economic Systems, Elsevier, vol. 39(3), pages 413-422.
    3. Olga Biedova & Victoria Steblovskaya, 2020. "Multiplier Optimization For Constant Proportion Portfolio Insurance (Cppi) Strategy," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-22, March.
    4. Peyman Alipour & Ali Foroush Bastani, 2023. "Value-at-Risk-Based Portfolio Insurance: Performance Evaluation and Benchmarking Against CPPI in a Markov-Modulated Regime-Switching Market," Papers 2305.12539, arXiv.org.
    5. Vera Ivanyuk, 2022. "Proposed Model of a Dynamic Investment Portfolio with an Adaptive Strategy," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
    6. Thai Nguyen & Mitja Stadje, 2018. "Optimal investment for participating insurance contracts under VaR-Regulation," Papers 1805.09068, arXiv.org, revised Jul 2019.
    7. Tawil, Dima, 2018. "Risk-adjusted performance of portfolio insurance and investors’ preferences," Finance Research Letters, Elsevier, vol. 24(C), pages 10-18.
    8. Chen, An & Hieber, Peter & Nguyen, Thai, 2019. "Constrained non-concave utility maximization: An application to life insurance contracts with guarantees," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1119-1135.

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    More about this item

    Keywords

    Capital guarantee products; Constant proportion portfolio insurance; Option based portfolio insurance; Pension funds; Jump processes; Time-changed Brownian motion; Dynamic replication in discrete time; Utility theory; Certainty equivalent return;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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