Paper: arXiv 2610.14120

Authors: Ravil Akhtyamov

Abstract

A defined-benefit pension is only as safe as its sponsor, yet sponsor distress is under-instrumented relative to plan-side modelling. We present a transparent, reproducible early-warning pipeline built entirely on public data. A Sponsor Vulnerability Index (SVI), a gradient-boosted classifier over point-in-time SEC EDGAR balance-sheet fundamentals and two macro series, predicts a filings-based distress state one to two quarters ahead. On 36 U.S. sponsors in five sector groups (1,418 firm-quarters, 2015Q1-2025Q3) it reaches an out-of-fold AUC-ROC of 0.887 and PR-AUC of 0.711 (base rate 11.9%) under leave-one-firm-out cross-validation. A Monte Carlo VaR with a stylized transition-stress overlay shows that climate-type stress is negligible for a diversified plan but adds 20-43% to one-year 95% VaR when 22.5% of assets are held in sponsor securities. A dynamic self-investment cap maps the SVI to a limit that falls from 8% to below 1% in acute distress and recovers with the sponsor, which we illustrate on PG&E’s 2019 bankruptcy and Boeing’s persistent fragility. We report the method’s failure modes alongside its results (book-equity labels that also fire on non-credit events such as spin-offs, positives concentrated in one firm, and stylized stress parameters) and release code, data and results under a concept DOI.

Complexity vs Empirical Score

  • Math Complexity: 5.0/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents a robust empirical framework for sponsor distress prediction using public data, demonstrating strong predictive performance. While the mathematical underpinnings are standard (gradient boosting, VaR), the application and integration into a dynamic cap mechanism show significant practical rigor and novelty. The commitment to reproducibility is also a strong point.

Research Flowchart

  flowchart TD
    A[Research Goal: Early Detection of Pension-Sponsor Distress] --> B{Key Methodology Steps};

    B --> C[1. Sponsor Vulnerability Index (SVI) Development];
    B --> D[2. Stress-Augmented VaR Modeling];
    B --> E[3. Dynamic Self-Investment Cap Design];

    C --> F[Data: SEC EDGAR Filings, Macro Series];
    D --> F;

    F --> G{Computational Processes};
    G --> H[Gradient-Boosted Classifier (SVI)];
    G --> I[Monte Carlo Simulation (VaR)];
    G --> J[Rule-Based Mapping (Cap)];

    H --> K[Key Findings: SVI (AUC-ROC 0.887, PR-AUC 0.711)];
    I --> L[Key Findings: Stress adds 20-43% to VaR with Self-Investment];
    J --> M[Key Findings: Dynamic Cap (8% to <1% in distress)];
    K & L & M --> N[Outcomes: Transparent, Reproducible Early-Warning Pipeline];

    style A fill:#D0E0F0,stroke:#333,stroke-width:2px;
    style N fill:#D0E0F0,stroke:#333,stroke-width:2px;