Robust Asset-Liability Management

ArXiv ID: 2310.00553 “View on arXiv”

Authors: Unknown

Abstract

How should financial institutions hedge their balance sheets against interest rate risk when managing long-term assets and liabilities? We address this question by proposing a bond portfolio solution based on ambiguity-averse preferences, which generalizes classical immunization and accommodates arbitrary liability structures, portfolio constraints, and interest rate perturbations. In a further extension, we show that the optimal portfolio can be computed as a simple generalized least squares problem, making the solution both transparent and computationally efficient. The resulting portfolio also reduces leverage by implicitly regularizing the portfolio weights, which enhances out-of-sample performance. Numerical evaluations using both empirical and simulated yield curves support the feasibility and accuracy of our approach relative to existing methods.

Keywords: Interest Rate Risk, Immunization, Ambiguity-Averse Preferences, Generalized Least Squares, Liability Management, Fixed Income

Complexity vs Empirical Score

• Math Complexity: 8.0/10
• Empirical Rigor: 6.0/10
• Quadrant: Holy Grail
• Why: The paper employs advanced mathematical concepts like the Gateaux differential, saddle point problems, and functional analysis, while also providing numerical evaluations using empirical yield curves and out-of-sample performance metrics.

  flowchart TD
    A["Research Goal"] --> B["Methodology"]
    B --> C["Data & Inputs"]
    C --> D["Computation"]
    D --> E["Findings"]

    A --> A1["How to hedge interest rate risk for long-term assets & liabilities?"]
    
    B --> B1["Ambiguity-Averse Preferences"]
    B --> B2["Generalizes classical immunization"]
    
    C --> C1["Empirical Yield Curves"]
    C --> C2["Simulated Yield Curves"]
    C --> C3["Liability Structures & Constraints"]
    
    D --> D1["Generalized Least Squares Problem"]
    D1 --> D2["Implicit Regularization"]
    D2 --> D3["Leverage Reduction"]
    
    E --> E1["Transparent & Efficient Portfolio"]
    E --> E2["Enhanced Out-of-Sample Performance"]