Group 1 - The optimistic expectation hypothesis previously suggested that the electric equipment sector is likely to lead the market [1] - The current market development is approaching the optimistic hypothesis, with a horizontal structure and shrinking fluctuations indicating a potential upward breakout [1] - A significant signal for an upward breakout would be surpassing the highest price on October 29, with trading volume exceeding the maximum bearish volume on October 30 [1] Group 2 - The leading sector has already confirmed a breakout [2] - The probability of an upward trend is high, particularly for the leading stock in the electric equipment sector, Ningde Times, which has shown a clear breakout after a typical VCP base [3] - Increasing positions in the electric equipment sector is considered an active strategy as the likelihood of upward movement significantly increases [3] Group 3 - Despite the growing evidence of a positive market, the possibility of a downward shift cannot be ruled out until the average price index fully breaks out [4]

Group 1 - The securities market is viewed as a probability game with a win-loss distribution of approximately seven losses, two draws, and one win, which raises questions about why many are drawn to it despite low winning odds [1] - The disparity in winning probabilities leads to significant potential returns, influencing participants' beliefs and behaviors in the market [1] - The article discusses two schools of thought regarding probability: frequentism, which views probability as an objective and unchanging reality, and Bayesianism, which sees it as a subjective belief that can be adjusted based on new evidence [1][2] Group 2 - Frequentism is characterized as a conservative approach that emphasizes safety margins, utilizing extensive data to extract objective rules and minimize risk, while Bayesianism is more intuitive and flexible, updating conclusions based on prior knowledge and current evidence [2] - The article suggests that no participant in the stock market is purely a frequentist or Bayesian; rather, individuals blend both approaches, adjusting their strategies based on varying frequencies of data and personal beliefs [2] - The integration of both frequentist and Bayesian thinking is essential for navigating the complexities of the market, allowing for the recognition of patterns while remaining adaptable to uncertainties [2][3] Group 3 - The analogy of chess is used to illustrate the combination of frequentism and Bayesianism, exemplified by AlphaGo's success in defeating top human players through a blend of data analysis and real-time strategy adjustments [3]

Core Viewpoint - The article discusses the contrasting investment philosophies of Warren Buffett and Charlie Munger, emphasizing Munger's more aggressive and rationalist approach compared to Buffett's experience-based skepticism [2][19]. Group 1: Investment Philosophies - Munger's investment style often challenges traditional experience-based methods, as seen in his investments in companies like BYD and Alibaba, which Buffett does not endorse [2][19]. - The article outlines two main philosophical approaches in investing: rationalism, which seeks to create a perfect explanatory system for market behavior, and empiricism, which relies on real-world experience and observation [12][13]. Group 2: Rationalism - Rationalism is characterized by a belief in knowledge derived from logical reasoning and innate ideas, as exemplified by philosophers like Descartes and Spinoza [8][9]. - The article highlights that many investment theories, particularly technical analysis, are rooted in rationalist principles, aiming to explain market movements through established frameworks [10][11]. Group 3: Empiricism - Empiricism, led by thinkers like Bacon, emphasizes knowledge gained from experience and observation, often using inductive reasoning to form theories [13][14]. - The limitations of empiricism are noted, particularly in investment contexts where past experiences may not apply to future scenarios, leading to potential risks [14][15]. Group 4: Skepticism - Skepticism, particularly as articulated by David Hume, questions the reliability of causal relationships, suggesting that what is perceived as causation may simply be correlation [15][16]. - Buffett embodies this skeptical approach, focusing on businesses he understands and avoiding complex financial models that rely on unproven assumptions [18][19]. Group 5: Practical Implications - The article concludes that while rationalism may attract financial elites seeking comprehensive systems, empiricism aligns more closely with the practical realities of high-risk investment activities [21][22]. - A successful investment strategy may not require exhaustive knowledge of all market dynamics but rather a focus on actionable insights derived from experience [22].

在连续二十几期的情绪观察之后，不知道读者是什么体会，我自己总结了一下主要是以下几点： 因此，比较稳妥的策略是： 关于情绪指标的延伸阅读： 关于动量指标的延伸阅读： 《 RSR（RSV、RPS）和趋势模板的背景含义 》 市场的日常是非理性的，因此会有波动起伏；市场又是很理性的，因为非理性终究要回归。 所谓循环和规律，只是对历史数据的统计归纳，如果生搬硬套必然犯刻舟求剑的毛病。总结用归纳法，实战用演绎法。交易演绎法，不是用归纳得到的经 验去求必然因果，而是不断评估大局和局部的胜率和赔率，更新自己的对策，西洋学说称之为贝叶斯主义。 择时的本质是情绪管理。 市场起伏在统计学上有迹可循，始终循环，但不简单重复； 方向可以预期，但无法准确预测，尤其无法预测涨跌幅度； 大多数周期，回撤比上涨要快，也即浮盈很容易变成浮亏； 胜率在情绪爬升期，赔率在情绪冰点，情绪高温区二率皆输； 动量背离是情绪反转前兆，动量的本源就是情绪; 情绪的最小张力单元就是TR，向上或者向下突破TR预示情绪反转； 1. 冰点抓胜率和赔率双赢，极端超卖区域的快速反弹； 2. 40周期情绪爬升过程中，抓更短周期的情绪回落点的胜率（埃尔德的三重滤网）； 3. ...