RDP 2026-03: Designing an Efficient Reference Rate: Lessons from SOFIA 5. Conclusions

This paper evaluates the determinants of noise in interest rate benchmarks, using Beta SOFIA. We estimate noise in Beta SOFIA at both the daily and transaction levels and identify the market and benchmark design factors that are significantly related to noise.

First, we find that Beta SOFIA exhibits higher noise when trading activity is concentrated, market liquidity is low, or a large share of transactions involve related parties. These conditions amplify the risk that the rate deviates from efficient market pricing, even in the absence of manipulation.

Second, transaction-level regressions confirm that related-party trades systematically contribute more noise than trades between unrelated parties. Similarly, trades that dominate daily volumes (i.e. have high market share) tend to introduce more noise into the rate. In contrast, higher transaction size is associated with reduced noise, suggesting that large trades in deep markets convey more reliable pricing information.

Third, we simulate several benchmark designs by applying alternative trimming techniques and excluding small-value transactions. Among the variants tested, a 25/95th percentile trimming delivers the largest and statistically significant reduction in benchmark noise. This suggests that benchmark precision could be improved through well-calibrated data filtering.

Our findings highlight three key elements that would help support a robust benchmark:

• Make the reporting of related-party transactions mandatory and exclude them from SOFIA calculations to reduce both noise and the potential for manipulation.
• Introduce expert judgement when market trading is thin or highly concentrated, to preserve rate integrity and informational efficiency on illiquid days.
• Consider extending the trimming window (e.g. 25/95th percentile trimming) and applying a minimum trade-size filter to strike a better balance between robustness and representativeness.

The Australian Securities Exchange has already adjusted its SOFIA methodology to reflect most of these findings, in preparation for the potential transition of SOFIA from its beta phase to a live benchmark.