Russell 3000 short interest and financing trends
06 January 2026
Sam Pierson, director of research at S3 Partners, looks at how integrating short selling data into Bloomberg's Tearsheet offers a single, intuitive workflow
Image: Shutterstock
Highlights
• Rising short demand: Notional short interest continued climbing into year-end.
• Financing dynamics: Broad squeezes and single-name catalysts keep revenue elevated and volatile.
• Positioning persists despite returns: Short interest grows even as the index posts strong gains.
• Rising prices alongside higher short interest suggest that meaningful gross exposure has been rebuilt since the April market low. Russell 3000 index and notional shorts are at an all-time-high.
The Russell 3000 provides a broad lens on US equity finance activity, and S3 short interest and securities finance data within Bloomberg’s Tearsheet (TRST) surfaces these dynamics in a single, intuitive workflow. By aggregating short-interest, borrow-cost, and price signals at the index level, it turns complex data into a clear narrative of how positioning and financing pressures evolve in real time. This note uses that framework to contextualise recent trends across the broader market.
Daily financing trends
Figure 1 shows the total value of short positions in the Russell 3000 and the daily financing revenue those positions generate. Short interest has climbed steadily through 2025, rising from about US$1.2 trillion at the start of the year, to roughly US$1.5 trillion by the end, signaling stronger demand to borrow and short stocks. Daily financing revenue, however, has been much more volatile, driven by sharp moves in individual names and market-wide squeezes in hard-to-borrow stocks. Together, these trends show how the Tearsheet captures the link between rising borrow demand and the changing cost of shorting across the index.
Short interest vs. market performance
This companion chart tracks average short interest as a percent of float against the one-year equal-weighted return of the Russell 3000. Over the past year, that index has gained about 12.5 per cent, while average short interest has risen from roughly 5.0 per cent to 6.3 per cent, showing that investors continued adding short exposure even as prices moved higher. This pattern suggests a cautious form of risk-on positioning, with hedge funds increasing gross exposure by expanding both their long and short books.
Integrating these signals in workflow
Together, these charts provide a clean view of how borrow demand, financing costs, and market performance interact across the index. Alongside the visual trends, the TRST dashboard surfaces top borrow rates, largest week-over-week fee movers, and names with the sharpest utilisation increases, giving users a real-time sense of where constraints and crowding are building. Using S3’s BQL-enabled fields within TRST, clients can extend this analysis to utilisation shifts, fee dynamics, volume signals, and squeeze risk, building a more complete picture of short-interest behaviour and its underlying drivers across any index on Bloomberg terminal.
Figure 1. Source: Bloomberg Terminal Tearsheet {TRST }
Figure 2. Source: Bloomberg Terminal Tearsheet {TRST }
• Rising short demand: Notional short interest continued climbing into year-end.
• Financing dynamics: Broad squeezes and single-name catalysts keep revenue elevated and volatile.
• Positioning persists despite returns: Short interest grows even as the index posts strong gains.
• Rising prices alongside higher short interest suggest that meaningful gross exposure has been rebuilt since the April market low. Russell 3000 index and notional shorts are at an all-time-high.
The Russell 3000 provides a broad lens on US equity finance activity, and S3 short interest and securities finance data within Bloomberg’s Tearsheet (TRST) surfaces these dynamics in a single, intuitive workflow. By aggregating short-interest, borrow-cost, and price signals at the index level, it turns complex data into a clear narrative of how positioning and financing pressures evolve in real time. This note uses that framework to contextualise recent trends across the broader market.
Daily financing trends
Figure 1 shows the total value of short positions in the Russell 3000 and the daily financing revenue those positions generate. Short interest has climbed steadily through 2025, rising from about US$1.2 trillion at the start of the year, to roughly US$1.5 trillion by the end, signaling stronger demand to borrow and short stocks. Daily financing revenue, however, has been much more volatile, driven by sharp moves in individual names and market-wide squeezes in hard-to-borrow stocks. Together, these trends show how the Tearsheet captures the link between rising borrow demand and the changing cost of shorting across the index.
Short interest vs. market performance
This companion chart tracks average short interest as a percent of float against the one-year equal-weighted return of the Russell 3000. Over the past year, that index has gained about 12.5 per cent, while average short interest has risen from roughly 5.0 per cent to 6.3 per cent, showing that investors continued adding short exposure even as prices moved higher. This pattern suggests a cautious form of risk-on positioning, with hedge funds increasing gross exposure by expanding both their long and short books.
Integrating these signals in workflow
Together, these charts provide a clean view of how borrow demand, financing costs, and market performance interact across the index. Alongside the visual trends, the TRST dashboard surfaces top borrow rates, largest week-over-week fee movers, and names with the sharpest utilisation increases, giving users a real-time sense of where constraints and crowding are building. Using S3’s BQL-enabled fields within TRST, clients can extend this analysis to utilisation shifts, fee dynamics, volume signals, and squeeze risk, building a more complete picture of short-interest behaviour and its underlying drivers across any index on Bloomberg terminal.
Figure 1. Source: Bloomberg Terminal Tearsheet {TRST }
Figure 2. Source: Bloomberg Terminal Tearsheet {TRST }
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