# Bài viết Liên quan Psychology

Trung tâm Tin tức HTX cung cấp những bài viết mới nhất và phân tích chuyên sâu về "Psychology", bao gồm xu hướng thị trường, cập nhật dự án, phát triển công nghệ và chính sách quản lý trong ngành tiền kỹ thuật số.

The Market Trades on Expectations, But You're Waiting for Answers

The market trades on expectations, not on waiting for answers. A common misconception is that prices react after data is released. In reality, sensitive capital moves based on anticipated changes in policy, capital flows, and sentiment. Once an expectation forms, prices adjust in advance. For example, if the market expects the Federal Reserve to cut interest rates, assets like gold, growth stocks, or BTC may rise ahead of the actual announcement. When the cut finally happens, the market might show little movement or even pull back—not because the news isn't significant, but because it was already priced in. The same applies to reports like non-farm payrolls. If weak employment data is anticipated, gold and bonds may rally beforehand. When the data confirms the weakness, prices may not rise further, as it merely validates existing expectations. This explains why markets sometimes appear irrational: good news doesn't always lift prices, and bad news doesn't always cause declines. The key is to assess whether an event was already anticipated and whether capital has begun to price it in or is now taking profits. The market is always trading the future, not the present. Price movements reflect bets on what comes next. Therefore, focusing solely on headlines can lead to losses. Instead, investors should ask: Was this news already expected? Is the market still pricing it in, or is it time to cash out? In short, the market doesn't wait for answers—it acts on the future it believes in, often long before the news becomes public.

marsbit07/03 01:27

The Market Trades on Expectations, But You're Waiting for Answers

marsbit07/03 01:27

The More Lifelike the Robot, the More Terrifying? Unveiling the 'Uncanny Valley Effect' in the Era of Humanoid Robots

As humanoid robots become increasingly lifelike, they confront a significant psychological barrier known as the "Uncanny Valley Effect," a concept proposed by Japanese roboticist Masahiro Mori in 1970. This phenomenon describes a dip in human comfort and acceptance when robots appear almost, but not perfectly, human. Minor imperfections in facial expressions, eye movements, or skin texture trigger a subconscious sense of unease, as the brain detects something trying, yet failing, to mimic a person. Examples range from the controversial human-like robot Sophia to animated characters in films like *The Polar Express*. The effect poses a key design challenge for robotics companies. Some, like Boston Dynamics, avoid it entirely by creating highly capable but visibly mechanical robots. Others, like Hanson Robotics, push for greater human likeness despite the risk. For consumer robots, especially in homes, most manufacturers opt for stylized or clearly mechanical designs to ensure broader acceptance. While the Uncanny Valley remains a powerful force, its impact may diminish over time through technological advancements that achieve near-perfect realism or through generational familiarity as people grow accustomed to interacting with humanoid machines. Ultimately, navigating this psychological frontier requires as much understanding of human perception as of robotics technology itself.

marsbit06/09 06:07

The More Lifelike the Robot, the More Terrifying? Unveiling the 'Uncanny Valley Effect' in the Era of Humanoid Robots

marsbit06/09 06:07

Wang Chuan: After Investing in Storage Stocks and Seeing a Thirty-Fold Return, How to Remain Unanxious (Part 7) - A Quarter-Century Cycle

Wang Chuan: Reflections on Investment Anxiety and Market Cycles After Observing a 30x Gain in a Storage Stock (Part 7) – A Quarter-Century Cycle This article examines the cyclical nature and inherent risks in technology hardware investments, using the storage and semiconductor sectors as examples. It criticizes the misleading practice of "annualized" Net Dollar Retention (NDR) rates, where short-term growth is extrapolated unrealistically. A key concept explored is "reflexivity" – demand driven by panic, exploration, and liquidity during market booms, which can vanish just as quickly when conditions reverse. This reflexivity exists both in product demand and among speculative stock buyers, creating powerful feedback loops that inflate prices during upturns and exacerbate crashes during downturns. The author highlights a major risk for hardware sectors: unlike assets with defined cycles (e.g., Bitcoin's halving), there's no guarantee of a swift recovery post-crash. Companies like Micron, Intel, and Cisco took roughly a quarter-century to surpass their 2000 highs, enduring drawdowns exceeding 80%. This is attributed to the "bullwhip effect" in supply chains, where demand collapses instantly but过剩产能 persists, and a migration of narrative-driven capital. High-valuation stories吸引 speculative funds during growth phases, but these funds quickly depart for the next hot narrative once growth slows, leaving behind stronger companies with much lower valuations. The piece warns of dangerous mental models formed during bull markets: 1) equating current strong demand with perpetual high growth, and 2) believing that making fast, large profits is easy. Citing巴菲特, the author notes that easy money undermines rationality, likening speculators to Cinderella at a ball with a clock that has no hands. The current phase presents an asymmetric risk-reward scenario: potential for further gains exists, but the downside risk is an 80%+ drawdown and a multi-decade wait for breakeven, which reflexive speculators cannot tolerate. The hypothetical investor "老王" (Lao Wang), who achieved a 30x return, is used to illustrate potential pitfalls. Leverage could lead to a wipeout during a sharp correction. Even without leverage, ingrained beliefs in easy money would likely lead him to double down after losses, expecting a quick rebound. Instead, he might face a protracted decline, depleting his resources through frantic trading as the high-growth narrative fades. The conclusion references Schopenhauer, comparing those who have seen multiple market cycles to an audience seeing the same magic trick repeatedly—once the illusion is understood, its power is gone.

marsbit06/09 02:16

Wang Chuan: After Investing in Storage Stocks and Seeing a Thirty-Fold Return, How to Remain Unanxious (Part 7) - A Quarter-Century Cycle

marsbit06/09 02:16

Wang Chuan: How to Avoid Anxiety When the Neighbor, Lao Wang, Made Thirty Times His Investment in Storage Stocks (7) - A Quarter-Century Cycle

Wang Chuan: Reflections on a Quarter-Century Cycle – How to Stay Calm After a 30x Gain on Storage Stocks (Part 7) This article continues the discussion on investment pitfalls. It highlights the deceptive use of metrics like the "Annualized Net Dollar Retention Rate" by some companies to inflate growth projections. The core analysis focuses on the "reflexivity" present in both product demand and financial markets during boom periods. In a bubble, speculative and fear-driven demand in the real economy interacts with speculative, leveraged buying in financial markets, creating a powerful upward feedback loop. This dynamic reverses sharply when faced with physical or liquidity constraints, leading to a cascading downturn. The hardware and semiconductor sectors face unique risks. Unlike assets with defined cycles, there's no guarantee of a swift recovery post-crash. Historical examples like Micron, Intel, and Cisco show it can take decades to surpass previous peaks after severe drawdowns (80-95%). This is due to the "bullwhip effect" in supply chains—demand vanishes quickly while过剩产能 persists—and the migration of speculative capital and growth narratives to new sectors once momentum slows. Companies may have stronger fundamentals years later, but the speculative "soul" of extreme valuations is long gone. The author warns of psychological traps for new investors: mistaking temporary, intense demand for permanent growth, and believing that making quick, large profits is easy. Citing Buffett, the piece cautions that easy money erodes rationality. The current phase presents an asymmetric risk-reward scenario: potential for further gains versus the risk of an 80%+ drawdown and a multi-decade recovery wait—an outcome reflexive speculators cannot endure. The hypothetical "Lao Wang" who made 30x may be wiped out by leverage or, driven by the "get-rich-quick" mindset, may repeatedly try to recover losses until exhausted, failing to recognize that the high-growth narrative has ended. The piece concludes with Schopenhauer's analogy: those who've seen multiple cycles are like an audience watching the same magic trick repeatedly—the illusion no longer works.

链捕手06/09 02:02

Wang Chuan: How to Avoid Anxiety When the Neighbor, Lao Wang, Made Thirty Times His Investment in Storage Stocks (7) - A Quarter-Century Cycle

链捕手06/09 02:02

Cyber Chumaxian: Fake Taoists, AI Fortune-Telling, and the Forgotten Mysticism of Northeast China

"Cyber Shamans: Fake Taoists, AI Fortune-Telling, and the Untold Story of Northeast China’s Occultism" For millennia, the Chinese have developed complex metaphysical systems—from oracle bone divination to the I Ching and Four Pillars of Destiny—to seek security in an uncertain world. Despite modern technology’s attempt to replace superstition with rationality, AI has ironically become occultism’s latest tool. Recent crackdowns exposed fake Taoists using AI to answer existential queries, while apps like CeCe attract millions with free AI fortune-telling, later charging for live “spiritual” consultations. At the heart of this fusion is Northeast China, where Shamanic and “Chumaxian” traditions (based on animal spirits possessing humans) have evolved into a robust industry. Historically rooted in hardship—from the migration waves of “Chuang Guandong” to post-industrial unemployment—Northeastern metaphysics thrives on uncertainty. Today, it offers what many call “therapy tailored for the Chinese soul”: externalizing blame through cosmic narratives (e.g., bad luck years or evil spirits), unlike Western psychology’s inward focus. AI accelerates this shift. With algorithms now matching expert diviners in accuracy, low-end fortune tellers are being replaced. Meanwhile, prompt-savvy “metaphysical engineers” use AI to generate readings, focusing only on emotional delivery. Live-streamed “cyber shamans” combine folksy warmth with AI-generated scripts, offering cheap comfort in anxious times. This trend has even gone global. Startups like FateTell sell AI-translated Chinese astrology reports to overseas users, repackaging “feudal superstition” as Eastern philosophy for Silicon Valley elites. Yet behind the rise of AI mysticism lies a deeper human yearning—for certainty in an unstable world. As regulations tighten on AI divination, the core demand remains: whether through shamans or algorithms, people still seek comfort when facing the unknown.

marsbit03/30 02:08

Cyber Chumaxian: Fake Taoists, AI Fortune-Telling, and the Forgotten Mysticism of Northeast China

marsbit03/30 02:08

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