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A Large-Scale Optimization Model for Replicating Portfolios in the Life Insurance Industry

Author

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  • Maximilian Adelmann

    (Department of Business Administration, University of Zurich, 8032 Zurich, Switzerland)

  • Lucio Fernandez-Arjona

    (Department of Business Administration, University of Zurich, 8032 Zurich, Switzerland)

  • Janos Mayer

    (Department of Business Administration, University of Zurich, 8032 Zurich, Switzerland)

  • Karl Schmedders

    (IMD Lausanne, 1001 Lausanne, Switzerland)

Abstract

Replicating portfolios have emerged as an important tool in the life insurance industry, used for the valuation of companies’ liabilities. This paper describes the replicating portfolio (RP) model used to approximate life insurance liabilities in a large global insurance company. We describe the challenges presented by the latest solvency regimes in Europe and how the RP model enables this company to comply with the Swiss Solvency Test. The model minimizes the L 1 error between the discounted life insurance liability cash flows and the discounted RP cash flows over a multiperiod time horizon for a broad range of different future economic scenarios. A numerical application of the RP model to empirical data sets demonstrates that the model delivers RPs that match the liabilities and perform well for economic capital calculations.

Suggested Citation

  • Maximilian Adelmann & Lucio Fernandez-Arjona & Janos Mayer & Karl Schmedders, 2021. "A Large-Scale Optimization Model for Replicating Portfolios in the Life Insurance Industry," Operations Research, INFORMS, vol. 69(4), pages 1134-1157, July.
    • Handle: RePEc:inm:oropre:v:69:y:2021:i:4:p:1134-1157
    DOI: 10.1287/opre.2020.2098
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    Keywords

    finance: portfolio; financial institutions: insurance; programming: linear; OR Practice; insurance regulation; liability cash flows; linear programming; out-of-sample tests; replicating portfolios; Solvency II;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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