a16z：从代币模型挑战谈起，如何设计新经济模型解锁现金流和合规性

长文源：区块律动Published on 2010-08-24Last updated on 2024-08-10

Software Stocks Scared by AI, How Did They Suddenly Become the Hottest Spot in the U.S. Stock Market?

Software stocks, once feared to be doomed by AI, have staged a dramatic comeback, posting their largest two-day outperformance against the S&P 500 in 25 years. Stocks like Snowflake and Datadog surged over 50% in days, fueled by strong earnings that countered earlier panic. The narrative that AI would render traditional software obsolete has flipped. Reports show AI isn't replacing software but becoming a major user of it, requiring databases, security platforms like Okta, and workflow tools. The low hedge fund positioning in software, at a multi-year low, triggered a massive short squeeze and rally. Analysts now argue the profit wave is shifting from AI hardware to software, as companies integrate AI into complex, governed business processes. The key insight is that enterprises pay for the ability to turn AI "intelligence" into reliable, compliant business outcomes—a gap that established software companies are well-positioned to fill. AI isn't killing software; it's redefining its role and creating new demand.

marsbit9m ago

Software Stocks Scared by AI, How Did They Suddenly Become the Hottest Spot in the U.S. Stock Market?

marsbit9m ago

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.

marsbit10m ago

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

marsbit10m ago

For Hedging, Buy Gold and Oil; For Explosive Growth, Buy AI; Bitcoin, the 'Outdated' Asset, Enters a Bear Market

Bitcoin’s price has recently fallen sharply, hitting a two-month low near $66,000, with Ethereum also dropping to a three-month low. While surface explanations point to ETF outflows, geopolitical tensions, and corporate selling, a deeper issue is emerging: Bitcoin is losing a crucial asset competition. For years, Bitcoin thrived in a low-rate environment where investors sought alternatives amid inflation fears and dissatisfaction with traditional options. Now, the market landscape has shifted, leaving Bitcoin stuck in an "awkward middle ground," facing challenges on three fronts: 1. **As an inflation hedge, gold is winning.** Investors worried about persistent inflation are turning to tangible assets like gold, energy stocks, and commodity producers, which offer more direct pricing power and physical backing. 2. **For growth exposure, AI is winning.** Those seeking high growth now favor AI-related companies with actual revenues and profits, an area where Bitcoin's lack of cash flow puts it at a disadvantage. 3. **Within crypto, infrastructure and stablecoins are winning.** Even investors wanting crypto exposure have alternatives like exchanges, stablecoin issuers, and tokenization firms, whose performance is directly tied to real-world adoption and offers clearer operational leverage. The recent market reaction to inflation warnings highlights this shift. Instead of boosting Bitcoin as "digital gold," such news now drives flows toward traditional inflation-sensitive assets. Therefore, recent events like ETF outflows and corporate selling are seen not as causes, but as symptoms of this new reality. Capital has more compelling options, and investors are becoming more selective. The emerging bear case for Bitcoin is no longer about it being a fraud or failed technology, but rather that **scarcity alone is no longer enough**. It is no longer seen as the best hedge, the best growth asset, or the only crypto play.

marsbit26m ago

For Hedging, Buy Gold and Oil; For Explosive Growth, Buy AI; Bitcoin, the 'Outdated' Asset, Enters a Bear Market

marsbit26m ago

SaaS Battle Royale: The Survivors Who Win All Share One Common Trait

**Summary** The AI revolution has triggered a "SaaS apocalypse," forcing a brutal market shakeout. The key dividing line is the pricing model. Companies like Snowflake and Datadog, which charge based on consumption (e.g., data processed or compute used), are thriving. AI workloads actively *generate* more demand for their services, fueling growth. Datadog's accelerating revenue is a prime example. Microsoft and Palantir, as platform/ecosystem players, also benefit by acting as essential channels for AI deployment. In contrast, traditional SaaS firms built on per-seat or per-task licensing (e.g., Intuit, Adobe) face direct pressure, as AI threatens to automate the very human tasks their software supports. Companies like Salesforce, a per-seat giant, are caught in the middle. While showing strong AI monetization (e.g., its Agentforce platform) and experimenting with consumption-based "Flex Credits," its stock remains under pressure, illustrating that the market rewards *completed* transitions, not just the intent. The recent Microsoft Build conference underscored key trends: AI is evolving from an assistant to an autonomous "agent," and platform providers like Microsoft are consolidating their control. The market's recovery is highly selective, focused on identifying which companies are "fed by AI" versus "eaten by AI." Future focus will be on the diffusion of this recovery to transforming companies and the real-world adoption data of AI agents like Microsoft Copilot.

marsbit44m ago

SaaS Battle Royale: The Survivors Who Win All Share One Common Trait

marsbit44m ago

XRP Falters In Face Of Rival XLM: Why Retail Traders Are Dumping One For The Other

Rival cryptocurrencies XRP and XLM are seeing a shift in retail trader preference, particularly in South Korea. Data from the Upbit exchange shows XLM's 24-hour trading volume ($252.3M) has surpassed XRP's ($125.7M) for the first time. This shift is attributed to increased interest in Stellar's role in tokenized finance, fueled by news linking the network to the US DTCC. While XLM's price surged over 55% to $11, XRP fell below $1.3 despite its historical popularity in Asian markets. A separate analyst suggests XRP could follow with a significant rally, potentially targeting new highs, though this remains speculative.

bitcoinist44m ago

XRP Falters In Face Of Rival XLM: Why Retail Traders Are Dumping One For The Other

bitcoinist44m ago

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