Mid-cap stocks are trading at an unusually wide discount to their larger counterparts, creating what one portfolio manager describes as a “truck-wide” opportunity for investors willing to look beyond the crowded mega-cap trade.
Amy Y. Zhang, portfolio manager of the Alger Mid Cap 40 ETF (FRTY), has highlighted that mid-cap stocks currently trade at a 30% discount relative to large caps, based on price-to-earnings ratios. Historically, mid-caps have traded at par or even a premium to large caps due to their faster growth potential.[1]
Investors have long favored a “barbell” approach, focusing portfolios on large-cap stocks supplemented with small-cap exposure while bypassing mid-caps entirely, according to Zhang. However, the valuation discount has widened more recently as early “AI Enablers”[2] concentrated in large-cap technology stocks drove larger gains in that segment of the market.
Yet mid-caps have delivered strong historical performance with attractive risk metrics. Over the past 30 years, mid-caps generated 11.2% annualized returns compared to 10.9% for large caps, while maintaining a similar risk-adjusted profile with a Sortino ratio of 0.80 versus 0.90 for large caps.[3]
Why the Environment May Be Shifting
Zhang points to the Federal Reserve’s transition from raising rates to cutting them as a potential catalyst for mid-cap outperformance. Mid-cap stocks are “long duration” assets that typically benefit during rate-cutting cycles. According to Zhang, lower rates should also spur merger and acquisition activity, which tends to favor mid-sized companies.
The changing macro backdrop comes as mid-caps trade with less analyst coverage than large caps, an inefficiency Zhang believes active managers can exploit. Large-cap companies in the S&P 500 average 24.5 analysts per stock, while mid-caps in the S&P MidCap 400 average just 13.5 analysts per stock, according to FactSet data from March[4].
Zhang believes there are many opportunities beyond traditional AI infrastructure plays, focusing on “AI Adopters” — mid-sized companies embedding artificial intelligence to expand margins or boost revenue. These firms remain largely undiscovered by Wall Street despite their potential.
FRTY takes a concentrated approach with approximately 40 holdings and an active share of 78% as of 12/31/25. The strategy seeks companies undergoing “Positive Dynamic Change” through factors like new management, product innovation, or regulatory shifts.
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[1] Source: FactSet. P/E is price divided by earnings per share over next 12-months, as of October 31, 2025.
[2] Alger defines AI Enablers as the companies developing the building block components for, and investing in, AI infrastructure such as machinery, hardware, software and services.
[3] Source: FactSet for the 30-year period ended December 31, 2024. Mid Caps represented by the Russell Midcap Index; Large Caps represented by the S&P 500.
[4] Source: FactSet as of March 2025. Large Caps represented by the companies in the S&P 500 Index and Mid Caps represented by the companies in the S&P MidCap 400 Index.
Disclosure Information
The views expressed are the views of Fred Alger Management, LLC (“FAM”) and its affiliates as of January 2026. These views are subject to change at any time and may not represent the views of all portfolio management teams. They should not be interpreted as a guarantee of the future performance of the markets, any security or any funds managed by FAM. These views are not meant to provide investment advice and should not be considered a recommendation to purchase or sell securities. Holdings and sector allocations are subject to change. Past performance is not indicative of future performance.
Risk Disclosures: Investing in the stock market involves risks, including the potential loss of principal. Growth stocks may be more volatile than other stocks as their prices tend to be higher in relation to their companies’ earnings and may be more sensitive to market, political, and economic developments. Investing in companies of medium capitalizations involves the risk that such issuers may have limited product lines or financial resources, lack management depth, or have limited liquidity. Companies involved in, or exposed to, AI-related businesses may have limited product lines, markets, financial resources or personnel as they face intense competition and potentially rapid product obsolescence, and many depend significantly on retaining and growing their consumer base. These companies may be substantially exposed to the market and business risks of other industries or sectors, and may be adversely affected by negative developments impacting those companies, industries or sectors, as well as by loss or impairment of intellectual property rights or misappropriation of their technology. Companies that utilize AI could face reputational harm, competitive harm, and legal liability, and/or an adverse effect on business operations as content, analyses, or recommendations that AI applications produce may be deficient, inaccurate, biased, misleading or incomplete, may lead to errors, and may be used in negligent or criminal ways. AI technology could face increasing regulatory scrutiny in the future, which may limit the development of this technology and impede the future growth. AI companies, especially smaller companies, tend to be more volatile than companies that do not rely heavily on technology. A significant portion of assets may be invested in securities of companies in related sectors, and may be similarly affected by economic, political, or market events and conditions and may be more vulnerable to unfavorable sector developments. Assets may be focused in a small number of holdings, making them susceptible to risks associated with a single economic, political or regulatory event than a more diversified portfolio. Active trading may increase transaction costs, brokerage commissions, and taxes, which can lower the return on investment. At times, cash may be a larger position in the portfolio and may underperform relative to equity securities.
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Sortino ratio is a risk-adjusted metric that measures an investment’s return relative to its downside risk.
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