Expert insight
June 17, 2026
Active investing is potentially rewarding, but it comes with challenges.
When drafting talent into a professional sports team, the front office wants to improve the team but typically has a limited salary budget. Top draft picks have the most talent, but studies show they are often overvalued given their expensive contracts. The ideal draft pick, whether taken in the first or last round, is one whose on-field performance exceeds the expectations of their salary.
Similarly, successful active investing is about finding a fund that can outperform the market by more than it charges in fees, leaving the end investor with attractive net-of-fee alpha. The most talented managers may not be the best investments if the price isn’t right.
After costs are accounted for, most active equity funds have underperformed over time.1 However, the rewards for selecting—and having the discipline to stick with—a successful active fund over the long term can be significant.
Investors and researchers have long sought active fund characteristics that have a reliable relationship with outperformance. Research from Vanguard’s Investment Strategy Group and our Oversight and Manager Search team’s extensive experience in selecting active equity managers for our funds highlight several quantitative and qualitative characteristics that can increase the likelihood of selecting a manager who can outperform.
Quantitatively, past performance, particularly over the short term, can be an unreliable signal.2 Instead, evaluating the underlying drivers of past performance and comparing managers to appropriate benchmarks and peer groups can determine if performance stemmed from luck or skill.3, 4
Using a sample of 1,600 U.S.-domiciled active equity funds, we evaluated four characteristics previously identified by researchers as being reliably connected with outperformance.5 Using data for the 33-year period from January 1990 through December 2022, we calculated the characteristics over distinct three-year periods starting with 1990–1992, and then assessed their ability to explain excess returns in the subsequent three-year period (1993-1995). We then repeated this process in subsequent three-year periods (1993–1995 to calculate characteristics and assess their ability to explain excess returns from 1996–1998) for the rest of the period. The adjacent figure shows the characteristics that displayed economically meaningful and statistically significant relationships with future performance. 6
Notes: The value for each fund characteristic is the estimated beta coefficient from a pooled regression model with future three-year annualized fund excess return versus the Morningstar-style benchmark as the dependent variable, style box and time-fixed effects, triennial observations, and standard errors clustered at the fund and time levels, while controlling for the systematic exposure of funds based on the Fama French (2018) six-factor model. Fund characteristics were standardized for the analysis, so the values can be compared based on the average economic size of the relationship with future three-year annualized excess return for a one-standard-deviation increase in the fund characteristic’s unit (except for fund AUM, because it required log transformation for testing). Underlying monthly data are for a sample of actively managed U.S. equity “nine box” funds and cover the period from January 1990 through December 2022. All variables are statistically significant at the 5% level. Past performance is no guarantee of future results.
Sources: Vanguard calculations, using data from Morningstar, Inc., and Kenneth French’s website, found at mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.
As previous Vanguard research suggests, cost is paramount in selecting a fund: The higher the costs, the higher the hurdle to outperforming a given benchmark net of fees.7, 8
Fund size is another key and interrelated consideration. While larger funds generally are lower cost and more likely to survive over time than their smaller counterparts, funds that grow too large relative to their investment universe or investment process can incur higher trading costs and find it difficult to take meaningful positions in less liquid stocks that may be mispriced.
Turnover reflects the extent to which a manager trades; all else equal, higher turnover translates into higher trading costs, such as commissions and market impact, which reduce returns. Like fund operating costs (expense ratios), the costs associated with higher turnover challenge outperformance. High-turnover funds can and do still outperform, particularly in more liquid market segments or with more diversified strategies, but the odds are lower.
Capture ratio is proxied by upside capture ratio divided by downside capture ratio, where upside (downside) capture ratio is the net return for a fund in the months during periods when the market, proxied by the S&P 500 Index, rose (fell) divided by the prospectus benchmark return in those same months (three-year average). This can be thought of as the ability of a manager to outperform in both up and down markets. A fund’s capture ratio tends to be more predictive of future performance than prior absolute returns alone. For example, a fund with 120% upside capture and 130% downside capture—a negative capture ratio—could have strong results amid a steady bull market but be less likely to succeed over a full market cycle, with the risk of significant underperformance in a bear market.
This group of four quantitative characteristics accounts for less than 20% of the variability in future relative performance. That still leaves more than 80% of the volatility in performance relative to a manager’s benchmark unexplained. That suggests that qualitative factors are also important to consider when selecting an active manager.
With 50 years of experience searching for and overseeing active managers, we believe that investors should consider the firm, the fund strategy, the investment team, their investment philosophy, and their investment process.
People are paramount. Strong portfolio management teams tend to share several characteristics, including relevant training and credentials (for example, Chartered Financial Analyst/MBA), experience, and cohesion. Diversity within investment teams is also important. Vanguard research has shown that teams with strong credentials and diversity have tended to outperform.9 Firm-level factors such as resources, reputation, and incentive structures can shape a firm’s ability to attract, retain, and develop investment talent.
Philosophy and process are intertwined.10 A fund’s philosophy can be understood as what the managers look for in a stock—the market inefficiency they seek to exploit—and the investment process as how they go about exploiting it. Understanding both the economic rationale and the historical risk and return characteristics of a given philosophy helps contextualize results over time.
A fund’s investment process spans idea generation, research, portfolio construction, and trading. The clarity, discipline, and repeatability of these elements are key considerations. The research aspect is particularly important. Active investing is a highly competitive endeavor—company information is widely available and there are hundreds of smart, well-trained analysts following most larger-capitalization stocks. Consistently deriving an edge against this competition and developing a differentiated view on a company’s future requires thorough, proprietary research that goes well beyond simple headlines, publicly available financial ratios, or catchy themes.
The evaluation of an active strategy often comes down to two questions: “Has it worked in the past and will it continue to work in the future?” There is meaningful risk of investors failing to appreciate the cyclicality that besets even the most successful active managers over the long term, exposing them to underperformance if they buy near the peak of a strategy’s success or sell near its trough. Active fund investing requires discipline to realize its benefits.
Active equity fund investing remains a challenging endeavor, with relatively few managers delivering persistent outperformance after costs. The evidence suggests that both quantitative factors (such as cost, size, turnover, and capture ratios) and qualitative considerations (such as team, firm, people, philosophy, and process) play a role in shaping outcomes. For all investors, focusing on these criteria can improve the odds of selecting above-average active equity funds that can deliver more than they cost—like the general managers of sports teams drafting future all-stars in the latter rounds of a draft.
The authors would like to thank Doug Grim and Ning Yan for their invaluable quantitative and qualitative contributions to this commentary.
1 S&P Dow Jones Indices LLC, SPIVA® U.S. Scorecard, Year-end 2025. 2026. spglobal.com/spdji/en/documents/spiva/spiva-us-year-end-2025.pdf.
2 Chris Tidmore and Andrew Hon. Patience With Active Performance Cyclicality: It’s Harder Than You Think. The Journal of Investing, 2021, 30(4): 622.
3 Eugene F. Fama and Kenneth R. French. Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 1993, 33(1): 3–56.
4 Jonathan B. Berk and Richard C. Green. Mutual Fund Flows and Performance in Rational Markets. Journal of Political Economy, 2004, 112(6): 1269–1295.
5 We used a pooled regression approach to determine the association between equity funds’ future excess returns (average excess return relative to their Morningstar-assigned benchmarks over the subsequent three-year period, starting with 1993–1995) and the characteristics of the prior period. The model included 10,354 monthly observations.
6 The results shown in the figure are from a pooled sample. We performed a similar analysis using a balanced panel approach and found similar results. In addition to the four charted characteristics, we tested the information ratio, the peer-adjusted information ratio, number of holdings, cash weight, excess return, tracking error, fund r-squared, fund age, systematic activeness, and log of firm AUM. Information ratio, peer-adjusted information ratio, cash weight, tracking error, and fund age were not statistically significant. Average turnover was statistically significant at the 5% level. All others were statistically significant at the 1% level.
7 Andrew J. Patterson, Stephen Lawrence, and Marvin Ertl. Considerations for Active Fund Investing. Vanguard, 2024. workplace.vanguard.com/content/dam/inst/iig-transformation/insights/pdf/2024/considerations-for-active-investing.pdf
8 Andrew Patterson and Ning Yan. Are Investors Paying Too Much for their Risk Exposure? Vanguard, 2025. corporate.vanguard.com/content/corporatesite/us/en/corp/articles/are-investors-paying-too-much-risk-exposure.html
9 Stephen Lawrence. Diversity Matters: The Role of Gender Diversity on US Active Equity Fund Performance. SSRN, 2022. papers.ssrn.com/sol3/papers.cfm?abstract_id=4081494
10 For more detail on the importance of firm, people, philosophy, and process, please see Matthew J. Piro, CFA and Andrew M. Shuman, CFA’s Active Edge: Winning the Zero-sum Game, Vanguard, 2025 available at corporate.vanguard.com/content/dam/corp/research/pdf/active_edge_winning_the_zero_sum_game.pdf
Notes:
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