Damodaran divested from Tesla not due to overvaluation, but because consumer purchasing decisions became tied to political affiliation, introducing a layer of unpredictable risk that is difficult to analyze financially.
Sports franchises defy traditional valuation because they are not investments but 'trophy assets' for billionaires. Their prices are driven by the scarcity of teams relative to the growing number of billionaires who desire ownership, not by financial performance.
Instead of forecasting growth to justify a valuation, take a company's current market cap and work backward to find the implied revenue growth. This makes the market's embedded expectations explicit and easier to scrutinize.
Recent strength in assets like gold and crypto signals more than just an inflation hedge; it reflects a fundamental, widespread loss of trust in the entire financial system, from central banks to regulators and governments.
The historical outperformance of stocks has a standard error so large (2.1% on a 5.4% premium) that the true premium could be anywhere from 1% to 9%. This statistical uncertainty makes history an unreliable guide for future returns.
The primary concern with OpenAI isn't its high growth forecast, but its founder's inability to articulate a clear business model. This suggests a focus on stock price momentum over building a sustainable, long-term business.
Each major tech company is massively investing in AI because their overconfident leaders believe they will be the sole winner in a winner-take-all market. This guarantees collective overinvestment and large write-offs for the eventual losers.
A new class of company operates between private and public markets, accessing vast, public-style capital without the required corporate governance. This allows them to scale to immense valuations before developing a viable business model, creating novel risks.
Software's main competitive advantage isn't code, but its deep integration into customer data and workflows, creating high switching costs. AI threatens this moat by automating those integrated tasks, reducing customer stickiness and pricing power.
While MAG7 companies fund AI spending with cash flow, the real danger is other firms using debt, especially private credit. This transforms potential corporate failures from isolated events into systemic risks that can cause broader economic ripple effects.