In today’s risk-aware investment landscape, identifying latent sources of volatility and crowding is critical for both portfolio construction and stress testing. Building upon Ihor Dusaniwsky’s foundational work on battleground stocks, this research introduces a systematic approach for identifying securities with conflicting positioning between long and short investors. Using S3 Partners’ proprietary short interest and long interest datasets, we define and validate a quantitative signal, the Long-to-Short (LTS) Ratio, which captures the structural imbalance, long/short skews and conflict across active investor flows. This dual-sided view uniquely positions S3 to illuminate cross-positioning dynamics that traditional data sources cannot detect.

Battleground stocks are defined as those where the notional value of long and short positioning are roughly balanced (at or around 1:1 ratio), suggesting high investor disagreement and positioning conflict. These names are inherently more vulnerable to volatility shocks and de-grossing, making them essential for risk overlay analysis and hedge fund de-risking scenarios. These stocks—where both sides have substantial positions—are prone to volatility and sharp price dislocations depending on who capitulates.

We define the Long-to-Short Ratio (LTS Ratio) as follows:

Where:

LongInterestMV = Long Interest Shares × Price (USD)

ShortInterestNotional = Short Interest × Price (USD)

The LTS Ratio helps us to observe the imbalances of buying or selling pressure in a particular stock. Using this ratio, we can classify stocks into LTS regimes. As described in the earlier research, within the actively traded segment, long holdings ($13.2 trillion) outnumber short holdings ($1.55 trillion) by about 8.5:1. Although most stocks have relatively insignificant short selling relative to their long holdings there are stocks where short sellers do have an impact on price moves: the battleground stocks.

The key cohort of interest - the Battleground stocks - are defined as stocks with LTS Ratios between 0.65 and 1.35, indicating a balance of long and short active ownership - Identifying where active investors are in conflict. Creating a basket of approximately 60 names historically. This contrasts with directional regimes: LTS < 0.65: Short-dominated, LTS > 1.35: Long-dominated – where either Short or Longs are winning. By monitoring the daily cross-section of these regimes, we can track conflict evolution and incorporate it into a risk factor model.

Cumulative Returns

The following analysis covers the period from January 2021 to April 2025. Our universe is constrained to U.S. equities where both long and short active data are available (On average, the LTS universe includes approximately 1,700 names.).

The cumulative returns chart below illustrates performance by Long-to-Short (LTS) ratio groups, showing how systematically defined "Battleground Stocks" (LTS 0.65–1.35) compare with the Skewed Long stocks (LTS 10–50) - in other words where Longs are 10-50 times Shorts - and the Russell 3000 benchmark. The Battleground group exhibits distinct cyclicality, with heightened volatility and drawdowns during market stress, while the Skewed Long basket closely follows the benchmark.

Annualized Performance, Volatility Profile, Returns Distribution

While Battleground stocks generate comparable annualized returns to the benchmark over the period, their dramatically elevated volatility and drawdown profile introduce an asymmetric risk exposure. The annualized volatility of 44% is more than double that of the benchmark, with a maximum drawdown exceeding -62%, underscoring their sensitivity to deleveraging cycles and positioning risk.

In practical terms, this convexity may appeal to high-risk, high-reward trading strategies or hedging overlays—but from a core portfolio perspective, these names represent unrewarded volatility. The risk, for most institutional mandates, is not worth taking unless actively managed through a tactical lens.

Battleground Stocks’ return distribution exhibits fat tails and high dispersion on both sides. This reflects the inherently unstable nature of battleground stocks—those with conflicting institutional positioning. These names are more exposed to nonlinear shocks, resulting in high realized volatility and deep drawdowns.

While the Skewed Long Stocks exhibit the Distribution that is symmetrical like Russell 3000: bell-shaped, resulting in lower volatility, higher Sharpe, and greater trend persistence. The Russell 3000 distribution reinforces its role as a neutral benchmark. It lacks the tail risk and asymmetric skew observed in battleground names.

Risk Characteristics and Factor Correlation

Correlation analysis with style factor ETFs from iShares (IWV, MTUM, QUAL, VLUE, USMV, SIZE) reveals:

Moderate correlation with IWV and MTUM.

Lower correlation with USMV, underscoring these stocks' incompatibility with minimum volatility strategies.

These ETFs are commonly used as proxies for style or risk premia in quantitative and factor-based investing. Battleground stocks have lower correlation with the USMV iShares MSCI USA Min Vol Factor ETF that seeks to reduce risk by investing in lower-volatility U.S. equities

The high sensitivity of Battleground names to changes in fund positioning implies elevated “positioning beta.”

Where: IWV = iShares Russell 3000 ETF, MTUM = iShares MSCI USA Momentum Factor ETF, QUAL = iShares MSCI USA Quality Factor ETF, VLUE = iShares MSCI USA Value Factor ETF, USMV= iShares MSCI USA Minimum Volatility Factor ETF, SIZE = iShares MSCI USA Size Factor ETF

A few names from 4/28/25 snapshot show intense conflict between longs and shorts in active portfolios. Examples include:

Monitoring both sides of the ledger can help anticipate high‑momentum plays and manage risk around rapid market reversals.

Use Cases for Risk Management

Pre-emptive Monitoring: Flag sudden changes in LTS ratio or inclusion into the Battleground cohort to pre-empt crowding reversals. Risk teams can monitor the daily composition of the Battleground basket and deploy it as a dynamic exclusion list during periods of elevated market fragility. Rapid shifts in positioning—such as a stock moving into or out of the 0.65–1.35 LTS window—can act as early warning signals of volatility clusters or positioning stress. In this way, the framework serves not only as a reactive diagnostic but also as a volatility sensor embedded within exposure management.

Conclusion

Systematically identifying Battleground stocks via the LTS Ratio provides an edge for risk-aware investors. These stocks serve as a live barometer for institutional disagreement and are primed for inflection points. Integrating this framework into risk models and overlays enhances preparedness for nonlinear price behavior and portfolio fragility.

Equally important is the ability to detect stocks outside the Battleground range—particularly those classified as Skewed Long (high LTS ratios) or Skewed Short (low LTS ratios). These cohorts reflect strong directional risk and can expose portfolios to thematic performance chases or short squeezes. Continuous LTS monitoring not only enables tactical risk control around battleground names but also sharpens awareness of where asymmetric positioning could lead to instability or illiquidity under stress.

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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.