The Reddit Rally stock episodes of 2021 exposed a critical blind spot in traditional risk management frameworks: short-side exposure to securities with extreme borrow costs and constrained supply. None of the risk models accounted for extreme short squeeze events that aren’t within a normal standard distribution. In such dislocations, shorts on hard-to-borrow names can inflict asymmetric losses, particularly when crowd sentiment triggers forced covering. This paper introduces a systematic “Specials Basket” framework, identifying the most short-constrained and expensive-to-borrow names, providing a forward-looking indicator of where the next short squeeze may emerge. Drawing from S3 Partners' daily short interest and validated by the Drechsler & Drechsler (2014) shorting premium research, we make the case for integrating “Specials” exposure into daily risk dashboards and portfolio stress testing practices.

Using a Russell 3000 proxy universe, we construct our “Specials” or hard-to-borrow (HTB) basket as the intersection of stocks in Quintile 5 of both:

Utilization % (Short Interest / Total Lendable Quantity) – stocks with the highest utilization

Offer Rate (Market composite financing fee paid by hedge funds for settled short positions) - stocks with the highest borrow costs

On average, the basket includes about 100 names. These names exhibit the most extreme combination of borrow scarcity and cost burden. During the Q1 2021 meme squeeze window, the Specials Basket significantly outperformed as retail momentum triggered broad short covering in these highly shorted names. The basket is volatile and uncorrelated with the rest of the market, making it difficult to track and manage using traditional risk management tools.

The Specials Basket and Short-Side Fragility

This cohort aligns with Drechsler & Drechsler’s high-fee segment, which their research shows carries a measurable shorting premium.Their research shows that these names carry a ‘shorting premium’ due to the concentrated risk borne by arbitrageurs. In our risk management framework, this translates to heightened squeeze vulnerability and convex losses when sentiment flips. By integrating Specials or hard-to-borrowexposure into portfolio monitoring, risk managers can proactively manage tail risks that traditional factor models miss.

While most U.S. equities can technically be shorted, a Specials Basket can behave as if shorting is severely constrained. As Miller (1977) theorized, when pessimistic views cannot be acted upon, prices can become inflated. Modern studies show that these constraints don’t fully explain long-term anomalies, but in short-term dislocations, such as squeezes or crowded trades, they can allow mispricings to persist and even accelerate. For risk managers, this reinforces the need to monitor Specials exposure—not just for performance drag, but for latent convexity in stress scenarios.

Netflix’s docuseries 'Eat the Rich' recounted the explosive rise of GameStop (GME), including commentary from S3’s founder Bob Sloan, who highlighted the mechanics of how short squeezes develop and spread. Bob stresses that investment managers should not view this as an isolated episode. “Specials” and short squeeze episodes will always exist—and when market structure, crowd sentiment, and liquidity align—they can erupt into another unwind cycle. Tools like the S3’s short interest data let risk teams preemptively monitor the fuse.

Let’s revisit the data. Reddit Rally Leaders (12/31/2020 – 3/15/2021). These weren’t random spikes. They were Specials, showing up clearly on the utilization and borrow cost metrics months before the rallies peaked.

The next squeeze episode that we observed in the chart was early 2025 that peaked in February. It was led by this 2025 Squeeze Cohort (11/01/2024 – 2/18/2025). In the first quarter of 2025, prior to the escalation of tariff headlines, the U.S. stock market experienced a significant rally, largely driven by a short squeeze phenomenon. This rally was particularly pronounced in small- and mid-cap stocks, where high short interest led to rapid price increases as investors rushed to cover their positions.

Actionable Takeaways for Risk Managers

Short positions in “Specials” present a unique challenge: while they typically offer alpha, they also possess unmonitored convexity risk. They are option-like exposures with unbounded downside during stress. During stress events, losses are rapid and unbounded. Without explicit monitoring of your exposure to Specials or hard-to-borrow stocks, risk models remain blind to squeeze-prone concentrations. We recommend the following:

Integrate high short interest, rates and utilization into daily exposure reports

Stress test portfolios with hypothetical cost spikes or utilization surges based on historical shock event

Flag “Specials” ahead of catalysts (e.g., earnings, macro shifts)

Use “Specials” and hard-to-borrow exposure to refine stop-loss logic and capital at risk calculations

Use “Specials” as your exclusion list

The next squeeze may not be meme-driven—but it will likely emerge from the same mechanics: names that are expensive to borrow, heavily shorted, and capacity constrained. By integrating S3’s short interest data into risk oversight, managers can reduce blind spots and build resilience into short-side strategies. “Specials” isn’t just a basket—it’s a risk lens for the next volatility regime.

While hard-to-borrow (HTB) stocks are more prone to short squeezes, squeezes can and do occur across all sectors of the market—including among large-cap, liquid names. These events often stem from idiosyncratic risk—unexpected catalysts, sector-specific sentiment shifts, or single-stock news flow that makes them harder to predict. That’s where a structured framework helps. With S3’s short interest data, risk managers can build custom risk factors that separate systematic squeeze potential from one-off, unpredictable events. By creating a real-time “Specials” or HTB basket—you can build custom short interest risk framework to identify and flag stocks that are most susceptible to squeeze risk.

Want to know more? Access this data in real time using S3’s BLACK APP

The information herein (some of which has been obtained from third party sources without verification) is believed by S3 Partners, LLC (“S3 Partners”) to be reliable and accurate. Neither S3 Partners nor any of its affiliates makes any representation as to the accuracy or completeness of the information herein or accepts liability arising from its use. Prior to making any decisions based on the information herein, you should determine, without reliance upon S3 Partners, the economic risks, and merits, as well as the legal, tax, accounting, and investment consequences, of such decisions.