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Hedging goals

Author

Listed:
  • Thomas Krabichler

    (Eastern Switzerland University of Applied Sciences)

  • Marcus Wunsch

    (Zurich University of Applied Sciences)

Abstract

Goal-based investing is concerned with reaching a monetary investment goal by a given finite deadline, which differs from mean-variance optimization in modern portfolio theory. In this article, we expand the close connection between goal-based investing and option hedging that was originally discovered in Browne (Adv Appl Probab 31(2):551–577, 1999) by allowing for varying degrees of investor risk aversion using lower partial moments of different orders. Moreover, we show that maximizing the probability of reaching the goal (quantile hedging, cf. Föllmer and Leukert in Finance Stoch 3:251–273, 1999) and minimizing the expected shortfall (efficient hedging, cf. Föllmer and Leukert in Finance Stoch 4:117–146, 2000) yield, in fact, the same optimal investment policy. We furthermore present an innovative and model-free approach to goal-based investing using methods of reinforcement learning. To the best of our knowledge, we offer the first algorithmic approach to goal-based investing that can find optimal solutions in the presence of transaction costs.

Suggested Citation

  • Thomas Krabichler & Marcus Wunsch, 2024. "Hedging goals," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(1), pages 93-122, March.
    • Handle: RePEc:kap:fmktpm:v:38:y:2024:i:1:d:10.1007_s11408-023-00437-y
    DOI: 10.1007/s11408-023-00437-y
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    References listed on IDEAS

    as
    1. Ioannis Karatzas & Jaksa Cvitanic, 1999. "On dynamic measures of risk," Finance and Stochastics, Springer, vol. 3(4), pages 451-482.
    2. Johannes Ruf & Weiguan Wang, 2019. "Neural networks for option pricing and hedging: a literature review," Papers 1911.05620, arXiv.org, revised May 2020.
    3. Sid Browne, 1997. "Survival and Growth with a Liability: Optimal Portfolio Strategies in Continuous Time," Mathematics of Operations Research, INFORMS, vol. 22(2), pages 468-493, May.
    4. Eckhard Platen, 2005. "On The Role Of The Growth Optimal Portfolio In Finance," Australian Economic Papers, Wiley Blackwell, vol. 44(4), pages 365-388, December.
    5. Oleg Szehr, 2021. "Hedging of Financial Derivative Contracts via Monte Carlo Tree Search," Papers 2102.06274, arXiv.org, revised Apr 2021.
    6. Hans FÃllmer & Peter Leukert, 2000. "Efficient hedging: Cost versus shortfall risk," Finance and Stochastics, Springer, vol. 4(2), pages 117-146.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Goal-based investing; Quantile hedging; Efficient hedging; Deep hedging;
    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
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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