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  • SEC Approves FICC Rule Change to Improve Correlation Calculations in Bond Haircut Models for Enhanced Risk Management

SEC Approves FICC Rule Change to Improve Correlation Calculations in Bond Haircut Models for Enhanced Risk Management

  • By: Learn Laws®
  • Published: 03/12/2026
  • Updated: 03/12/2026

The Securities and Exchange Commission approved a proposed rule change from the Fixed Income Clearing Corporation on March 9, 2026, allowing enhancements to the correlation calculations used in bond haircut models for short-term securities. Filed on January 27, 2026, under Section 19(b)(1) of the Securities Exchange Act of 1934, the change addresses gaps in data for certain maturity buckets, enabling FICC to better manage credit risks in the U.S. Government securities market. Published in the Federal Register on February 3, 2026, the proposal received no public comments and aims to refine the Value at Risk charge methodology, potentially increasing aggregate margin requirements by a small percentage. This development underscores ongoing efforts by central counterparties to adapt risk models to evolving market data availability, ensuring more accurate coverage of potential losses from member defaults.

Background on FICC and Its Risk Management Framework

The Fixed Income Clearing Corporation operates as a central counterparty in the U.S. Government securities market, providing trade comparison, netting, risk management, and settlement services. By interposing itself between buyers and sellers, FICC assumes the risk of member defaults, which it mitigates through daily margin collections known as the Required Fund Deposit. This deposit, aggregated into a Clearing Fund, covers potential liquidation losses from a defaulting member's portfolio.

A core component of the margin is the Value at Risk Charge, which projects losses over a three-day liquidation period at a 99 percent confidence level using historical simulations. For securities with insufficient data, such as short-term bonds maturing in one year or less, FICC applies a haircut method. This groups bonds into maturity buckets and incorporates correlations to account for cross-bucket effects, typically drawn from fixed income indices provided by a designated vendor.

However, the vendor lacks data for specific buckets—Treasury 0-6 months, Treasury 6-12 months, and Treasury Inflation-Protected Securities 0-12 months—forcing FICC to assume zero correlations despite historical evidence of substantial intercorrelations. This practice, outlined in the GSD Methodology Document, has limited the model's ability to fully capture risk profiles, potentially underestimating required margins.

Details of the Proposed Rule Change

The approved changes amend the QRM Methodology Document to replace the zero-correlation assumption with data from an alternate vendor for the affected maturity buckets. This enables FICC to calculate more accurate correlations, reflecting actual market interdependencies. The proposal also removes outdated language on correlation alternatives and corrects a section reference for clarity.

FICC submitted an impact study covering September 1, 2024, to August 31, 2025, simulating the effects on Value at Risk Charges. Under normal conditions, the changes would have raised aggregate charges by an average of $46 million, or 0.09 percent, with a peak increase of $85 million, or 0.15 percent. Backtesting coverage remained stable at 99.85 percent. At the portfolio level, the average start-of-day charge increased by $0.22 million, or 0.09 percent, with the largest percentage rise at 14.52 percent for one portfolio.

If the backup Margin Proxy had been used—triggered by vendor data disruptions—the study projected an average aggregate increase of $88 million, or 0.16 percent, with a maximum of $163 million, or 0.38 percent. Portfolio-level impacts showed an average rise of $0.42 million, or 0.16 percent, with peaks up to 23.18 percent.

These adjustments align with FICC's rules under the Government Securities Division Rulebook, emphasizing risk-based margining without introducing new components.

Analysis of Implications and Regulatory Consistency

The rule change addresses a key limitation in FICC's risk model by incorporating alternate data sources, potentially leading to more precise margin requirements that better reflect short-term bond volatilities. From a legal perspective, it complies with Section 17A(b)(3)(F) of the Exchange Act, which mandates clearing agencies to promote prompt settlement and safeguard funds. By enhancing margin collection, FICC reduces the risk of depleting the mutualized Clearing Fund in a default scenario, limiting non-defaulting members' exposure.

The approval also meets standards under Rule 17Ad-22(e)(4)(i), requiring covered clearing agencies to maintain resources covering credit exposures with high confidence. The impact study's backtesting results support this, showing minimal disruption to overall coverage while addressing underestimations for short-term bonds.

Additionally, the change supports Rule 17Ad-22(e)(6)(i) by producing margin levels commensurate with product-specific risks. Perspectives vary: proponents view it as a necessary evolution in model accuracy, while some members might see higher margins as increasing operational costs. No comments were received, suggesting broad acceptance, though future scrutiny could arise if market conditions shift.

Precedents like the 2018 approval of FICC's Value at Risk floor (Securities Exchange Act Release No. 83362) highlight the SEC's emphasis on robust alternatives when primary data fails. Politically, this fits into broader regulatory efforts to strengthen financial infrastructure post-2008, without direct ties to executive actions.

Forward-Looking Considerations

This approval positions FICC to more effectively manage risks from short-term bond exposures, potentially setting a model for other clearing agencies facing data gaps. Ongoing monitoring of vendor data and backtesting will be essential to assess real-world performance. Debates may emerge on balancing model precision with margin affordability, especially in volatile markets. Future challenges include adapting to new data providers or regulatory updates, ensuring sustained alignment with evolving standards.

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