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Mathematical Analysis of Replication by Cash Flow Matching

Author

Listed:
  • Jan Natolski

    (University of Augsburg, Universitätsstraße 14, 86159 Augsburg, Germany)

  • Ralf Werner

    (University of Augsburg, Universitätsstraße 14, 86159 Augsburg, Germany)

Abstract

The replicating portfolio approach is a well-established approach carried out by many life insurance companies within their Solvency II framework for the computation of risk capital. In this note,weelaborateononespecificformulationofareplicatingportfolioproblem. Incontrasttothetwo most popular replication approaches, it does not yield an analytic solution (if, at all, a solution exists andisunique). Further,althoughconvex,theobjectivefunctionseemstobenon-smooth,andhencea numericalsolutionmightthusbemuchmoredemandingthanforthetwomostpopularformulations. Especially for the second reason, this formulation did not (yet) receive much attention in practical applications, in contrast to the other two formulations. In the following, we will demonstrate that the (potential) non-smoothness can be avoided due to an equivalent reformulation as a linear second order cone program (SOCP). This allows for a numerical solution by efficient second order methods like interior point methods or similar. We also show that—under weak assumptions—existence and uniqueness of the optimal solution can be guaranteed. We additionally prove that—under a further similarly weak condition—the fair value of the replicating portfolio equals the fair value of liabilities. Based on these insights, we argue that this unloved stepmother child within the replication problem family indeed represents an equally good formulation for practical purposes.

Suggested Citation

  • Jan Natolski & Ralf Werner, 2017. "Mathematical Analysis of Replication by Cash Flow Matching," Risks, MDPI, vol. 5(1), pages 1-15, February.
    • Handle: RePEc:gam:jrisks:v:5:y:2017:i:1:p:13-:d:91771
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    References listed on IDEAS

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    1. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    2. Mark Broadie & Yiping Du & Ciamac C. Moallemi, 2015. "Risk Estimation via Regression," Operations Research, INFORMS, vol. 63(5), pages 1077-1097, October.
    3. Ralf Korn & Manfred Schäl, 1999. "On value preserving and growth optimal portfolios," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 50(2), pages 189-218, October.
    4. Grosen, Anders & Lochte Jorgensen, Peter, 2000. "Fair valuation of life insurance liabilities: The impact of interest rate guarantees, surrender options, and bonus policies," Insurance: Mathematics and Economics, Elsevier, vol. 26(1), pages 37-57, February.
    5. Pelsser, Antoon, 2003. "Pricing and hedging guaranteed annuity options via static option replication," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 283-296, October.
    6. Bauer, Daniel & Bergmann, Daniela & Kiesel, Rüdiger, 2010. "On the Risk-Neutral Valuation of Life Insurance Contracts with Numerical Methods in View," ASTIN Bulletin, Cambridge University Press, vol. 40(1), pages 65-95, May.
    7. Lars Stentoft, 2004. "Convergence of the Least Squares Monte Carlo Approach to American Option Valuation," Management Science, INFORMS, vol. 50(9), pages 1193-1203, September.
    8. Eric Beutner & Janina Schweizer & Antoon Pelsser, 2013. "Fast Convergence of Regress-Later Estimates in Least Squares Monte Carlo," Papers 1309.5274, arXiv.org, revised Apr 2014.
    9. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    10. Lars Stentoft, 2004. "Assessing the Least Squares Monte-Carlo Approach to American Option Valuation," Review of Derivatives Research, Springer, vol. 7(2), pages 129-168, August.
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    Cited by:

    1. Patrick Cheridito & John Ery & Mario V. Wuthrich, 2021. "Assessing asset-liability risk with neural networks," Papers 2105.12432, arXiv.org.
    2. Patrick Cheridito & John Ery & Mario V. Wüthrich, 2020. "Assessing Asset-Liability Risk with Neural Networks," Risks, MDPI, vol. 8(1), pages 1-17, February.
    3. Luca Regis, 2017. "Special Issue “Actuarial and Financial Risks in Life Insurance, Pensions and Household Finance”," Risks, MDPI, vol. 5(4), pages 1-2, December.
    4. Hampus Engsner & Kristoffer Lindensjo & Filip Lindskog, 2018. "The value of a liability cash flow in discrete time subject to capital requirements," Papers 1808.03328, arXiv.org.
    5. Hampus Engsner & Kristoffer Lindensjö & Filip Lindskog, 2020. "The value of a liability cash flow in discrete time subject to capital requirements," Finance and Stochastics, Springer, vol. 24(1), pages 125-167, January.

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