Unlike physical sciences where observation doesn't change the subject, the stock market's behavior is influenced by participants watching it. A market can rise simply because it has been rising, creating momentum loops. This "self-awareness" means price and value are not independent variables, a key distinction from more rigid scientific models.

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Speculative manias, like the AI boom, function like collective hallucinations. The overwhelming belief in future demand becomes self-fulfilling, attracting capital that builds tangible infrastructure (e.g., data centers, fiber optic cables) long before cash flows appear, often leaving lasting value even after the bubble bursts.

Following George Soros's theory of reflexivity, markets act like thermostats, not barometers. Rising AI stock prices attract capital, which further drives up prices, creating a self-reinforcing loop. This feedback mechanism detaches asset values from underlying business fundamentals, inflating a bubble based on pure belief.

Phenomena like bank runs or speculative bubbles are often rational responses to perceived common knowledge. People act not on an asset's fundamental value, but on their prediction of how others will act, who are in turn predicting others' actions. This creates self-fulfilling prophecies.

Contrary to the popular belief that markets are forgetful, the speaker argues they are more traumatized by crashes (like 2008) than buoyed by bull runs. The constant crisis predictions and "Big Short" memes on social media demonstrate a powerful, persistent memory for loss over gain.

Moving from science to investing requires a critical mindset shift. Science seeks objective, repeatable truths, while investing involves making judgments about an unknowable future. Successful investors must use quantitative models as guides for judgment, not as sources of definitive answers.

Quoting G.K. Chesterton, Antti Ilmanen highlights that markets are "nearly reasonable, but not quite." This creates a trap for purely logical investors, as the market's perceived precision is obvious, but its underlying randomness is hidden. This underscores the need for deep humility when forecasting financial markets.

The most important market shift isn't passive investing; it's the rise of retail traders using low-cost platforms and short-term options. This creates powerful feedback loops as market makers hedge their positions, leading to massive, fundamentals-defying stock swings of 20% or more in a single day.

Contrary to intuition, widespread fear and discussion of a market bubble often precede a final, insane surge upward. The real crash tends to happen later, when the consensus shifts to believing in a 'new economic model.' This highlights a key psychological dynamic of market cycles where peak anxiety doesn't signal an immediate top.

A clear statement from a financial leader like the Fed Chair can instantly create common knowledge, leading to market movements based on speculation about others' reactions. Alan Greenspan's infamous "mumbling" was a strategic choice to avoid this, preventing a cycle of self-fulfilling expectations.

Marks emphasizes that he correctly identified the dot-com and subprime mortgage bubbles without being an expert in the underlying assets. His value came from observing the "folly" in investor behavior and the erosion of risk aversion, suggesting market psychology is more critical than domain knowledge for spotting bubbles.