Robust long-term interest rate risk hedging in incomplete bond markets

Sally Shen*, Antoon Pelsser, Peter Schotman

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Pricing ultra-long-dated pension liabilities under the market-consistent valuation is challenged by the scarcity of the long-term market instruments that match or exceed the terms of pension liabilities. We develop a robust self-financing hedging strategy which adopts a min–max expected shortfall hedging criterion
to replicate the long-dated liabilities for agents who fear parameter misspecification.We introduce a backward robust least squares Monte Carlo method to solve this dynamic robust optimization problem. We find that both naive and robust optimal portfolios depend on the hedging horizon and the current
funding ratio. The robust policy suggests taking more risk when the current funding ratio is low. The yield curve constructed by the robust dynamic hedging portfolio is always lower than the naive one but is higher than the model-based yield curve in a low-rate environment.
Original languageEnglish
Pages (from-to)273-300
Number of pages28
JournalJournal of Pension Economics & Finance
Volume20
Issue number2
Early online date5 Jun 2020
DOIs
Publication statusPublished - Apr 2021

JEL classifications

  • c61 - "Optimization Techniques; Programming Models; Dynamic Analysis"
  • g11 - "Portfolio Choice; Investment Decisions"
  • e43 - Interest Rates: Determination, Term Structure, and Effects

Keywords

  • Least squares Monte Carlo
  • Parameter uncertainty
  • incomplete market
  • liability valuation
  • robust optimization
  • least squares Monte Carlo
  • parameter uncertainty
  • Incomplete market

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