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Why Not Short Even When Bearish? Munger Did the Math on a 'Losing Trade'

Why Not Short Even When Bearish? Charlie Munger's Calculated "Loss-Making Account" Many traders, drawn to speculative tools like futures contracts, often face repeated failures. As the article notes, unless one is a genius, such instruments should be avoided for long-term profit-seeking. Similarly, the practice of short selling is viewed with caution. The author firmly states a policy of not shorting, even when bearish, preferring to simply wait. The core reason? Successful short selling requires exceptionally difficult conditions to profit. Legendary investors Warren Buffett and Charlie Munger have themselves reflected on painful short-selling experiences. Munger highlights two critical flaws in the mathematical logic of shorting: 1. Asymmetrical Risk/Reward: A long position has a maximum loss of 100% but unlimited upside. A short position caps profit at 100% (if a stock falls to zero) but carries theoretically unlimited loss potential. 2. The "Promoter" Problem: Fraudulent or struggling companies can prolong their decline. As Munger said, "You can run out of money before the promoter runs out of ideas," meaning short sellers may be forced to cover positions at a loss before the company's true fate unfolds. The article cites Stanley Druckenmiller, a famed hedge fund manager. He once shorted 12 companies that all eventually went bankrupt. However, intense market rallies forced him to cover his positions within three weeks, resulting in massive losses—$200 million of his capital plus an additional $600 million. He concluded he likely never made money shorting in his career. His experience perfectly illustrates Munger's points: facing unlimited losses and being wiped out before being proven right. The conclusion is clear: for most investors, complex instruments like short selling and derivatives are not viable paths to stable, long-term gains. Self-reflection is advised before repeatedly wasting time and capital on such speculative strategies.

marsbit06/03 02:35

Why Not Short Even When Bearish? Munger Did the Math on a 'Losing Trade'

marsbit06/03 02:35

MuleRun CTO: The Moat of Agents Lies in Data Density and User Memory

In a speech titled "Handing AI's Keys to the On-Chain Controllers," MuleRun CTO Shu Junliang discussed the evolution and security of AI Agents in finance and Web3. He outlined six dimensions for a complete AI assistant: dialogue, data input, agent capability, execution environment, user memory, and continuous learning. MuleRun's product integrates these through features like multi-platform IM bots, real-time multi-asset data, smart model routing, cloud sandboxes, persistent user profiles, and a shared knowledge network. Shu emphasized that while AI Agents are advancing from assisting to autonomously executing decisions—potentially enabling individuals to operate like small funds—safety remains paramount. He detailed MuleRun's security measures, including local key handling, isolated sandboxes, full audit trails, and strict permission controls. However, he acknowledged persistent risks like data exposure, model hallucinations, prompt injection, and the "black box" nature of AI decisions, advising manual confirmation for financial operations. He identified key trends: the shift from human-led to Agent-led on-chain interactions requiring infrastructure redesign; the erosion of information advantages replaced by competition in execution speed and strategy; and the balancing effect of Agents, which democratize access but ultimately advantage those with superior judgment. Shu concluded that an Agent's true moat lies in data density and accumulated user memory, not easily replicable technology, and that while Agents will reshape finance and Web3, human oversight over critical decisions must remain.

marsbit05/14 08:50

MuleRun CTO: The Moat of Agents Lies in Data Density and User Memory

marsbit05/14 08:50

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