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Saved January 06, 2026
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David George discusses the complexities of valuing high-growth companies, particularly those growing above 30%. He explains that conventional financial modeling struggles to account for sustained high growth, leading to undervaluation in the market. George emphasizes the importance of insights into products, markets, and people to identify potentially great companies.
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In his latest insight, David George from the a16z Growth fund highlights a critical observation about market perceptions of company growth rates, particularly those exceeding 30%. He notes that while his fund has achieved an impressive 112% growth with portfolio companies valued at 21 times revenue, the market often fails to fully appreciate high growth potential due to the difficulty of accurately modeling such trajectories. George points out that investors tend to adopt conservative forecasts, expecting growth rates to decline over time, which can lead to substantial undervaluation of rapidly growing firms.
George uses the example of Appleβs iPhone to illustrate this phenomenon, citing that consensus estimates were drastically lower than actual performance, exemplifying how even well-known companies can surprise investors with sustained growth. He argues that constructing financial models for companies with extraordinary growth is inherently challenging, as it goes against the natural tendency to predict a decline in growth rates. Instead, he believes that investors should focus on gaining insights into product, market, and people dynamics, which can provide a competitive edge in identifying exceptional growth opportunities.
Ultimately, George emphasizes his investment philosophy of paying fair prices for outstanding companies and underscores the importance of recognizing hidden greatness that others may overlook. His perspective suggests that growth-stage investing hinges significantly on the ability to understand and capitalize on high growth trajectories, which could lead to substantial returns if investors can look beyond traditional modeling constraints.
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