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Investor Julian Robertson of Tiger Global correctly identified the 2000 tech bubble but was forced to liquidate his fund just before it burst. This shows that even if you're right, a market bubble can inflate further and outlast your capital, making shorting it a perilous strategy.

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During the dot-com bubble, investors who sold at the first sign of a wobble missed massive gains. Analysis shows that even after the crash, buy-and-hold investors were profitable, while those who sold early were not. The worst financial outcome is panic-selling at the bottom of a crash, which locks in losses.

Even fundamentally sound companies get crushed when bubbles pop. Microsoft's stock took 17 years to recover its dot-com peak. Investors must consider the extreme opportunity cost of having capital tied up for over a decade just to break even, even if they believe in the company's long-term success.

Leopold Aschenbrenner's fund, despite a strong AI thesis, was margin called due to massive leverage. This shows how short-term market corrections, amplified by leverage, can destroy fundamentally sound, long-term positions—a classic lesson Warren Buffett has warned about for decades.

Investor Leopold Ashburner's bullish AI thesis may ultimately be proven correct. However, his fund was wiped out by a forced liquidation due to excessive leverage. This highlights that correct long-term predictions are worthless without proper risk management that can withstand short-term volatility.

Ray Dalio argues bubbles burst due to a mechanical liquidity crisis, not just a realization of flawed fundamentals. When asset holders are forced to sell their "wealth" (e.g., stocks) for "money" (cash) simultaneously—for taxes or other needs—the lack of sufficient buyers triggers the collapse.

History shows that markets can remain irrational longer than investors can remain solvent. For instance, the Nasdaq was 40% higher at its post-crash low in 2002 than when media first called the dot-com market "nutty" in 1995. Selling too early, even with sound analysis, often means missing substantial gains.

The dot-com era was not fueled by pure naivete. Many investors and professionals were fully aware that valuations were disconnected from reality. The prevailing strategy was to participate in the mania with the belief that they could sell to a "greater fool" before the inevitable bubble popped.

A market enters a bubble when its price, in real terms, exceeds its long-term trend by two standard deviations. Historically, this signals a period of further gains, but these "in-bubble" profits are almost always given back in the subsequent crash, making it a predictable trap.

While being a market Cassandra can build a reputation, being too early is costly. Charles Merrill of Merrill Lynch famously warned of a crash in 1928, but investors who heeded his advice missed a 90% market run-up before the October 1929 peak, illustrating the immense financial downside of exiting a bubble prematurely.

While the AI capex boom may seem unsustainable, the mechanics of shorting it (e.g., buying puts) reveal the extreme difficulty of the trade. The bet requires being correct not just on the eventual downturn but on its precise timing. The risk of losing the entire premium makes it an unattractive risk-adjusted bet.