Why low correlation and elevated dispersion create opportunity, but do not guarantee active outperformance
“It’s a stock-picker’s market.” – I know it sounds like the rallying cry of the active manager making a last stand against the passive rout. Bear with me!
The S&P 500 has spent four months going nowhere, the index rising 0.7% from the beginning of June to the beginning of October, with unusually low index volatility [1]. Yet beneath that quiet surface, individual stocks have been more volatile than average. The market appears calm not because its constituents are calm, but because their movements are so out of sync: stocks are moving in opposite directions much more than usual. That creates both an opportunity for stock-pickers and a potentially fragile calm.
Chart 1: S&P 500 Index – 30-day rolling volatility
Calm on the surface
Chart 2 shows the rolling three-month average correlation between each constituent’s returns and the S&P 500 falling to a historic low. This measures stock-to-index relationships. Low average correlation indicates weaker synchronisation with the market: company earnings, sector developments and investment themes matter more than the direction of the broader market and macroeconomic influences. This may be surprising given how rising bond yields (the stock market discount rate) and geopolitical events are dominating news headlines.
Chart 2: S&P 500 Index vs each index member – Average 3-month rolling correlation
It means that diversification has been unusually effective, but this protection is conditional. If a macroeconomic shock makes previously offsetting stocks move together, index volatility could rise sharply, even without a further increase in individual-stock volatility. Note: the vulnerability is a correlation shock, not necessarily an impending market fall.
It is also worth observing something further, the breakdown in the correlation between the S&P 500 Index and the S&P 500 Equal Weight Index. Both contain the same constituents, but the S&P 500 Index is behaving more like a concentrated active fund due to the dominance of a small number of holdings that account for over 40% of the index [2]. Passive allocation to the index now carries a substantial implicit bet on AI-related tech.
Chart 3: S&P 500 Index vs S&P 500 Equal Weight index – 3-month realised correlation
Different directions are not enough
Does low correlation make it a stock-picker’s market? No, low correlation alone does not in itself create a rewarding stock-picker’s market. Stock returns must also be sufficiently far apart; we need large differences in stock price movements. Dispersion measures that distance. Low correlations do not always mean high dispersion. For illustration, the table shows two scenarios where Stock A and B have zero correlation, but very different profiles of periodic returns. Scenario 1 returns are bounded between +0.7% and +1.3%, whereas scenario 2 returns are bounded between -14% and +16%.
Table 1: The distinction between correlation and dispersion
This year, we are experiencing a period of high stock dispersion, on a level greater than during the pandemic, while not yet at the TMT and GFC levels. For example, Moderna’s stock price rose 177% on 19 August, IBM dropped 25% on 14 July, Marvell Technology rose 33% on 2 June, Dell’s rose 33% on 29 May [3]. These are not small companies. This elevated dispersion is shown in Chart 4.
Chart 4: The S&P 500 Equal Weight Index – Dispersion
Higher dispersion raises both the rewards from picking winners and the cost of mistakes. It widens the range of active outcomes without creating skill or guaranteeing success, but gives skilled managers greater scope to demonstrate it.
When opportunity knocks
Anna von Reibnitz’s When Opportunity Knocks: Cross-Sectional Return Dispersion and Active Fund Performance (Critical Finance Review, 2017) examines active US equity mutual funds over 1972–2013, testing whether dispersion conditions the relationship between activeness and performance. In the study, ‘activeness’ is assessed by tracking three years of returns: the less a fund’s performance is explained by broad market styles like size, value, or momentum (measured as 1 − R²), the more ‘active’ the manager is considered.
[T]hose managers who pursue the most active strategies produce significant outperformance in times of high cross-sectional dispersion in returns. During times of high dispersion, a portfolio of the most active funds significantly outperforms a portfolio of the least active funds. This is in contrast to lower dispersion months, during which the difference in performance between the most and least active funds is not generally significant.
— Anna von Reibnitz
Crucially, the tests use observed dispersion to examine subsequent performance, drawing on the tendency for high dispersion to persist from month to month rather than requiring investors to anticipate its initial rise. As the paper explains, “our strategy does not require the ability to predict high dispersion before it first occurs, which is of significant value to fund managers and fund investors alike” (von Reibnitz).
The implication also runs backwards: “If a sample period is dominated by low dispersion and, consequently, low active opportunity, a skilled manager could appear to possess no skill based on performance alone” (von Reibnitz). This underscores the importance of evaluating performance in context.
Opportunity, not guaranteed
Capturing dispersion requires correct active bets, whether through skill or luck, and sufficient freedom to express them. Tight tracking-error budgets and closet indexing can leave little exposure to the opportunity. Today’s concentrated market creates a further complication. As Filippo Neumaier explains in The risk of measuring risk, a diversified active portfolio can now generate substantial tracking error simply because it differs from an increasingly concentrated benchmark. The very controls intended to limit risk may therefore restrict a manager’s ability to exploit the dispersion opportunity.
Position limits, liquidity requirements, diversification rules and factor-risk controls can further constrain active weights. Implementation matters too. Turnover, bid–ask spreads, market impact, taxes and slow execution can erode gross gains, so dispersion must be high enough to outweigh these costs.
Meanwhile, concentrated positions (that are not those of the benchmark) can increase drawdown, client-redemption and career risks, creating powerful incentives for managers to hug their benchmarks. Differentiating a portfolio therefore requires both individual conviction and an investment environment that allows it.
Amid ongoing pressure from passive alternatives, the current environment offers active managers a rare opening to demonstrate value. However, a ‘stock-picker’s market’ defines the breadth of opportunity rather than predicting success. Capturing those excess returns still requires skill, portfolio leeway, and the nerve to endure the inevitable discomfort of being different.
Sources
[1] Bloomberg, October 2026
[2] Bloomberg, October 2026
[3] Bloomberg
Key Information
No investment strategy or risk management technique can guarantee returns or eliminate risks in any market environment. Past performance is not a guide to the future. The prices of investments and income from them may fall as well as rise and investors may not get back the full amount invested. Forecasts and estimates are based upon subjective assumptions about circumstances and events that may not yet have taken place and may never do so. The statements and opinions expressed in this article are those of the author as of the date of publication, and do not necessarily represent the view of Redwheel. This article does not constitute investment advice and the information shown is for illustrative purposes only.
