Patient Capital Management is a Baltimore asset manager founded in 2020 by Samantha McLemore, CFA — Bill Miller's long-time co-manager (working together since 2002, running the flagship Opportunity Equity strategy since 2014). Continuing the Miller-school contrarian tradition, it practices "time arbitrage": exploiting behavioral mispricing to concentrate in controversial growth names (tech, healthcare, Bitcoin-related) at deep discounts to intrinsic value. Its site preserves Bill Miller's complete 1995-2022 market letters, alongside ongoing quarterly letters and webinars.
This investment firm values companies by estimating their future cash flows and discounting them to today—a classic approach it applies even to AI stocks. It isn’t for or against AI; instead it waits for prices to diverge from underlying business value. The firm says value investing isn’t about buying what looks cheap now, but spotting mispricing before others do. It mentions AI growth stocks and value stocks broadly, not naming specific companies. Its view is that AI names should pass the same valuation test as any other stock. Note: this is a promotional interview, not independent proof.
The author (Patient Capital) consistently anchors enterprise value to the present value of future free cash flows, neither avoiding nor blindly following AI stocks, and waits for opportunities where price diverges from fundamentals — a stance of 【Neutral】.
The article argues that Patient Capital measures a company's value not by short-term market narratives, but by the present value of its future free cash flows. Assistant Portfolio Manager Christina Siegel Malbon explained this framework in a Barron's interview titled "AI Stocks in a Value Fund? This Veteran Money Pro Says Absolutely": to determine how much a company is worth, first estimate its future free cash flows, then discount them back to today. The author's original words, "the value of any business is the present value of its future free cash flows," mean: "the value of any enterprise is the present value of its future free cash flows." This definition determines everything that follows — the valuation anchor is cash flow, not thematic hype.
The firm's view is that the essence of value investing is not to hold assets that look cheap today, but to identify divergences between market prices and business fundamentals before the opportunity becomes obvious. The author first rules out a common misunderstanding — the goal is not simply to hold assets that look cheap today — and then states the real objective in one sentence: "It is to identify where market prices have diverged from business fundamentals and to do so before the opportunity becomes obvious to others," meaning: "what it needs to do is identify where market prices diverge from business fundamentals and accomplish this before the opportunity becomes obvious to others." The article then sets out three execution premises: look forward, assess the durability of cash flows, and be willing to hold when the stock price is below the firm's estimate of long-term intrinsic value.
The article emphasizes that value investing is not about avoiding growth or innovation, but about applying valuation discipline to both; in an AI-driven market, this perspective is itself an advantage. On the AI theme specifically, Christina points out that when market expectations diverge from fundamentals, this framework supports holding companies that benefit from AI. In other words, the firm's stance on AI stocks is not a blanket bullish or bearish call, but a return to the second framework — evaluating opportunities when prices diverge from long-term value. The author describes this perspective as having become an asset in an AI-driven market. Note: this is a fund manager's self-assessment of its own strategy, and this article is a promotional piece for a Barron's interview published on the firm's official website, with no performance backtesting or third-party verification attached. Readers should treat this description as a methodological framework, not as performance evidence.
Actionable implication: In an AI-dominated market, value investors need not mechanically avoid AI stocks; instead, they should wait for the point where expectations diverge from long-term free cash flow value, evaluate growth stocks with the same valuation discipline they apply to value stocks, and accept the "not cheap" waiting period that may follow position-building. Note on institutional bias: This article is based on a Barron's interview, but it is essentially marketing content on Patient Capital's official website. Christina's account of her methodology provides no backtested data or independent verification, and reflects the perspective of a position holder.
| Target | Direction | Author's Stance in One Sentence | Key Data |
|---|---|---|---|
| AI Growth Stocks (broadly defined) | Not stated | Neither broadly bullish nor bearish; waits for a point where price diverges from long-term free cash flow value, then assesses with valuation discipline | No backtest or independent verification provided |
| Value Stocks (broadly defined) | Not stated | Does not pursue near-term cheapness; instead identifies opportunities where price diverges from fundamentals and sits below the estimated long-term intrinsic value | Valuation anchor is the present value of future free cash flows |