Counterpoint Global Insights Pattern Recognition
Counterpoint Global Insights 模式识别

CONSILIENT OBSERVER | December 13, 2023
CONSILIENT OBSERVER | 2023 年 12 月 13 日

In 1990, I was junior equity research analyst supporting a senior analyst who covered stocks in the food, beverage, and tobacco industries. After the market closed on June 7, ConAgra Inc (now Conagra Brands) announced it was acquiring the food operations of Beatrice Company. These included popular products such as Peter Pan peanut butter and Orville Redenbacher popcorn that gave Conagra access to a section of the supermarket where it had no presence.
1990 年，我是一名初级股票研究分析师，支持一位负责食品、饮料和烟草行业股票的高级分析师。6 月 7 日收盘后，康尼格拉公司（现康尼格拉品牌）宣布收购比阿特丽斯公司的食品业务。这些包括深受欢迎的产品，如彼得潘花生酱和奥维尔·雷登巴克爆米花，使康尼格拉能够进入其之前未涉足的超市部分。

Kohlberg Kravis Roberts & Co. (now KKR & Co.) had taken Beatrice private for more than billion in 1986, then the largest leveraged buyout in history. KKR quickly sold most of the conglomerate's divisions, including Avis Car Rental, Coca-Cola Bottling, and Tropicana. There were a lot of lookers, but no takers, for the food business at the price KKR sought.
高盛公司（现在的 KKR 公司）在 1986 年以超过 亿美元的价格将 Beatrice 公司私有化，这是当时历史上最大的杠杆收购。KKR 迅速出售了该企业集团的大部分部门，包括安飞士汽车租赁、可口可乐饮料和特罗皮卡纳果汁。对于 KKR 寻求的食品业务价格，有很多人围观，但没有人接受。

The assets that remained at Beatrice were desirable, but the accounting for the purchase made it "something of a white elephant." 3 Under purchase accounting, the buyer would have to assume billion in "unallocated purchase cost," effectively goodwill, that it would have to amortize over 40 years. This meant an accounting charge against earnings of nearly million per year that most companies preferred to avoid.
在 Beatrice 留下的资产令人向往，但购买的会计处理使其成为“一头白象”。根据购买会计，买方必须承担 亿美元的“未分配购买成本”，实际上是商誉，需要在 40 年内摊销。这意味着几乎每年要计入几乎 百万美元的会计费用，大多数公司都希望避免这种情况。

Beatrice sold for billion and the assumption of about billion in debt, less than one-half of what KKR had hoped for originally. But Conagra structured the payment to be tax efficient for the sellers, and the annualized return on the equity in the Beatrice LBO was reported to be as high as 50 percent.
贝嘉蕾以 亿美元出售，并承担约 亿美元的债务，远低于 KKR 最初希望的一半。但康尼格拉结构了付款方式，以使卖方获得税收效益，据报道贝嘉蕾 LBO 的股权年化回报率高达 50%。

Conagra arranged for information packets about the deal to be delivered to Wall Street analysts after the close of the market (this was before the dawn of the commercial internet). The senior analyst handed me the packet as he headed out the door and asked me to do the analysis. He indicated he would update his thoughts on the stock at the morning call the next day.
康尼格拉安排在市场收盘后向华尔街分析师发送有关交易的信息包（这是在商业互联网出现之前）。高级分析师在离开时把信息包交给我，并要求我进行分析。他表示他会在第二天的早间电话会议上更新对该股票的看法。

Michael J. Mauboussin michael.mauboussin@morganstanley.com
迈克尔·J·莫布森 michael.mauboussin@morganstanley.com

Dan Callahan, CFA 丹·卡拉汉，特许金融分析师

The analysis did not take long. Beatrice appeared to be a good strategic fit for Conagra, and the cash flows showed that the deal created value for shareholders despite the potential impact of goodwill amortization. Indeed, Conagra's management correctly understood goodwill amortization as an accounting rather than an economic cost. 6
分析并没有花费太长时间。贝娅特丽丝似乎是康尼格拉的一个很好的战略匹配，现金流显示，尽管商誉摊销的潜在影响，这笔交易为股东创造了价值。事实上，康尼格拉的管理层正确地将商誉摊销视为会计成本而非经济成本。

The senior analyst came in the next morning and said he was downgrading the stock based on his experience. He was a Wall Street veteran and recognized a pattern. There were two things that made him pessimistic about the stock's potential reaction to the news: the fact it was an acquisition and the possible drag on earnings from amortization. Most merger and acquisition (M&A) deals fail to create value for the acquiring company, and a hit to earnings is perceived to be bad.
高级分析师第二天早上走进来，表示他根据自己的经验正在将该股票评级下调。他是一位华尔街资深人士，能识别出一种模式。有两件事让他对该股票对消息的潜在反应感到悲观：一是这是一笔收购交易，二是摊销对收益的可能拖累。大多数并购交易未能为收购公司创造价值，而对收益的打击被视为不利。

Conagra's stock rose about 4 percent that day and the S&P 500 fell roughly 1 percent. The S&P 500 is an index that tracks the stocks of 500 of the largest companies listed in the U.S.
康尼格拉的股价当天上涨约 4％，标准普尔 500 指数下跌约 1％。标准普尔 500 指数是跟踪美国上市的 500 家最大公司股票的指数。

This report is about the powers and perils of pattern recognition. Investors and investment organizations regularly cite pattern recognition as the basis for action. While it can be extremely powerful and useful when applied appropriately, it can also be highly misleading and furnish fuel for overconfidence when used inappropriately.
这份报告涉及模式识别的力量和危险。投资者和投资机构经常将模式识别作为行动的基础。 当适当应用时，它可以非常强大和有用，但如果不当使用，也可能极具误导性，并为过度自信提供燃料。

We will define pattern recognition, discuss when it tends to work well, review why it may be misleading, and offer some ways to help improve it.
我们将定义模式识别，讨论何时它往往表现良好，审查为什么它可能具有误导性，并提供一些帮助改进它的方法。

The Merriam-Webster dictionary defines "pattern" as "a reliable sample of traits, acts, tendencies, or other observable characteristics of a person, group, or institution" and "recognize" as "to acknowledge or take notice of in some definite way."8 So pattern recognition is an awareness that what is happening now has happened in the past and offers a predictable sense of what's going to happen in the future. Investors with experience commonly sense they recognize patterns because they have a mental database of events and outcomes.
韦氏词典将“模式”定义为“一个人、团体或机构的特征、行为、倾向或其他可观察特征的可靠样本”，将“认识”定义为“以某种明确方式承认或注意到”。因此，模式识别是一种意识，即现在发生的事情过去曾发生过，并提供了对未来会发生什么的可预测感。有经验的投资者通常会感觉到他们认识到了模式，因为他们拥有一套事件和结果的心理数据库。

Pattern recognition works at the intersection of intuition and expertise. Intuition is the immediate sense of understanding something without conscious thought. In fact, Herbert Simon, a polymath who made major contributions to computer science, economics, and cognitive psychology, stated flatly that, "Intuition is nothing more and nothing less than recognition."10
模式识别工作在直觉和专业知识的交汇处。 直觉是对某事的即时理解，不经过意识思考。事实上，赫伯特·西蒙（Herbert Simon）是一位博学多才的学者，对计算机科学、经济学和认知心理学做出了重大贡献，他直言不讳地说，“直觉无非就是识别而已。”10

Expertise can be described as "consistently superior performance on a specified set of representative tasks for a domain."11 Becoming an expert generally requires devoting a large amount of time to deliberate practice in an environment where there is unambiguous feedback. Experts perceive patterns in their domains, solve problems qualitatively, and answer problems much faster and represent them at a deeper level when compared to novices.
专业知识可以被描述为“在某一领域的一组代表性任务上表现出持续优越的表现。”成为专家通常需要在一个能够提供明确反馈的环境中投入大量时间进行刻意练习。专家能够感知领域中的模式，定性地解决问题，并且在与新手相比时更快地回答问题并以更深层次的方式代表它们。

The words experience and expertise share the same Latin root, but distinguishing between them is crucial. Gregory Northcraft, a social psychologist and professor emeritus at the University of Illinois, suggests the following difference: "There are a lot of areas where people who have experience think they're experts, but the difference is that experts have predictive models, and people who have experience have models that aren't necessarily predictive.
单词“经验”和“专业知识”有着相同的拉丁语根，但区分它们是至关重要的。伊利诺伊大学的社会心理学家和名誉教授格雷戈里·诺斯克拉夫特（Gregory Northcraft）建议以下区别：“有很多领域，那些有经验的人认为他们是专家，但区别在于专家拥有预测模型，而有经验的人拥有的模型未必具有预测性。

Experience leads to expertise only when there is learning guided by clear and timely feedback. In instances when there is wiggle room in assessing the quality of decisions, those with experience may talk a better game than those without experience but offer judgments that are in the aggregate no better than average. Expertise applies under a relatively narrow set of conditions.
经验只有在有清晰及及时反馈指导的学习过程中才能转化为专业知识。在评估决策质量存在一定余地的情况下，有经验的人可能比没有经验的人说得更好，但其判断整体上并不比平均水平更好。 专业知识适用于相对狭窄的一组条件。

Work on expert political judgment by Phil Tetlock, a professor of psychology at the University of Pennsylvania, makes this point emphatically. Tetlock had 284 experts make a total of 28,000 predictions associated with political and economic outcomes from 1984 to 2003. A majority of Tetlock's participants had doctorate degrees, and on average they had more than a dozen years of work experience. He defined an expert as someone who makes a living by providing advice regarding political or economic trends.
菲尔·泰特洛克（Phil Tetlock）是宾夕法尼亚大学心理学教授，他在专家政治判断方面的研究强调了这一点。 泰特洛克让 284 位专家在 1984 年至 2003 年间进行了总共 28,000 次与政治和经济结果相关的预测。泰特洛克的大多数参与者拥有博士学位，平均工作经验超过十几年。他将专家定义为靠提供关于政治或经济趋势建议谋生的人。

The forecasts by the experts were little better than chance and usually worse than those produced by simple extrapolation algorithms. Further, he found that predictions by the participants were commonly based on "casespecific hunches about causality that make some scenarios more 'imaginable' than others."16 They had experience but lacked predictive models that were accurate.
专家们的预测比随机猜测稍微好一点，通常比简单外推算法产生的预测更糟糕。此外，他发现参与者的预测通常基于“关于因果关系的个案直觉，使得某些情景比其他情景更具‘想象力’”。他们有经验，但缺乏准确的预测模型。

Tetlock's description of how the experts he studied came up with forecasts appears very similar to what investors do. For example, a survey of more than 250 holders of the Chartered Financial Analyst designation, more than half of whom had 15 years or more of experience, revealed that 92 percent agreed with the statement, "The ability to construct a coherent and complete 'story' with the facts of a situation is the most important task when making a decision or recommendation."17
Tetlock 对他研究的专家们如何提出预测的描述与投资者的做法非常相似。例如，对 250 多名持有特许金融分析师资格的人进行的调查显示，其中一半以上拥有 15 年或更长的经验，有 92%的人同意这样的说法：“在做出决策或建议时，能够用事实构建一个连贯完整的‘故事’是最重要的任务。”

Heuristics and biases are a central area of research in cognitive psychology. Heuristics are mental shortcuts, or rules of thumb, that people use to make judgments. In general, heuristics are useful because they are fast and often accurate. But heuristics can lead to biases, or departures from an ideal decision-making process.
启发式和偏见是认知心理学研究的一个核心领域。启发式是人们用来做判断的心理快捷方式或经验法则。总的来说，启发式很有用，因为它们快速且通常准确。但启发式可能导致偏见，或者偏离理想决策过程。

Tetlock's participants and the CFA charterholders both appear to use the representativeness heuristic. This is when a decision maker anticipates what will happen next based on an event, or events, that appear representational of the situation under consideration. This allows a forecaster to craft a compelling story. This heuristic is a form of intuition that introduces bias when events are not as correlated as the decision maker perceives.
Tetlock 的参与者和 CFA 持证人似乎都使用了代表性启发式。当决策者根据看似代表所考虑情况的事件或事件来预测接下来会发生什么时，就会出现这种情况。这使得预测者能够编织一个引人入胜的故事。当事件与决策者感知的相关性不高时，这种启发式会引入偏见。

Research shows that both intuition and expertise work in some settings and fail in others. Understanding where and why intuition and expertise are effective is essential for knowing when pattern recognition is effective.
研究表明，直觉和专业知识在某些情境下起作用，在其他情境下则失败。 了解直觉和专业知识何时何地有效是至关重要的，以便知道模式识别何时有效。

Gary Klein is a psychologist who is one of the leading advocates for the role of expert intuition in decision making. Daniel Kahneman, a psychologist who won the Nobel Memorial Prize in Economic Sciences, has shown how decisions based on intuition commonly depart from normative economic theory, especially in realms of uncertainty and risk. The two got together and worked on what Kahneman called his "most satisfying experience" in adversarial collaboration, defined as "a good-faith effort to conduct debates by carrying out joint research."22
加里·克莱因（Gary Klein）是一位心理学家，是专家直觉在决策中发挥作用的主要倡导者之一。 丹尼尔·卡尼曼（Daniel Kahneman）是一位心理学家，曾获得诺贝尔经济学奖，他展示了基于直觉的决策通常偏离规范经济理论，特别是在不确定性和风险领域。 这两位合作进行了卡尼曼称之为“最令人满意的经历”的对抗性合作，定义为“通过共同研究进行辩论的善意努力”。22

They found that intuitive expertise and pattern recognition tend to work well in stable environments where cause and effect are clear and participants can receive timely and accurate feedback. The classic example is chess. Skilled chess players can rapidly see which side of the board has an advantage and often quickly identify optimal,
他们发现，直觉专业知识和模式识别往往在稳定的环境中效果良好，其中因果关系清晰，参与者可以及时获得准确的反馈。经典例子是国际象棋。熟练的国际象棋选手可以迅速看出棋盘的哪一边具有优势，并经常迅速确定最佳选择。
or close to optimal, moves. Chess masters, roughly the top one percent of rated players, recognize telling patterns on the board based on groups of pieces, called "chunks." A chunk is effectively a unit of information that allows an expert to absorb lots of accurate cues about the game.
或接近最佳的走法。象棋大师，大约是排名前百分之一的玩家，根据棋盘上的棋子组成的“块”识别出关键模式。一个块实际上是一个信息单元，让专家能够吸收大量关于游戏的准确线索。

If stability and feedback are essential to successful pattern recognition, instability and unclear links between cause and effect show where pattern recognition fails. Robin Hogarth, a cognitive psychologist, distinguishes between "kind" and "wicked" environments. In kind environments, outcomes are indicative of the quality of the process and feedback is accurate and plentiful. In wicked environments, outcomes are a poor or misleading reflection of process because causal links are blurred.
如果稳定性和反馈对于成功的模式识别至关重要，那么不稳定性和因果关系不清晰表明模式识别失败的地方。认知心理学家罗宾·霍加斯区分了“善良”和“邪恶”环境。在善良环境中，结果表明了过程的质量，反馈准确且丰富。在邪恶环境中，结果对过程的质量反映不足或误导性，因为因果关系模糊不清。

Expert agreement is one way to assess the validity of intuitive expertise. In kind environments, experts tend to agree on cues and the appropriate decisions that follow. For example, chess masters are likely to identify similar moves as attractive.
专家协议是评估直觉专业知识有效性的一种方式。在某种环境中，专家往往会就线索和随之而来的适当决策达成一致。例如，国际象棋大师可能会认同相似的走法。

In wicked environments, the views of experts often vary substantially. For instance, the one-year forecasts of the level of long-term interest rates by economists are not much different from random. Predictions of stock market returns by strategists and executives also tend to be poor.
在恶劣的环境中，专家们的观点经常存在较大差异。例如，经济学家对长期利率水平的一年预测与随机预测并无太大不同。 策略师和高管对股市回报的预测也往往不准确。

James Shanteau, a professor of psychology, summarizes the conditions for good and poor expert performance (see exhibit 1). In reality, you can think of expert performance across a continuum, from excellent to close to random. Shanteau adds some other relevant considerations. One is access to decision support systems. For instance, weather forecasters make very accurate short-term forecasts and largely agree with one another because they use sophisticated models that predict atmospheric conditions. But strategists or economists with equal credentials will have varying views on the probability of a recession or the price of oil one year from now.
詹姆斯·尚托（James Shanteau）是一位心理学教授，总结了优秀和糟糕专家表现的条件（见附件 1）。实际上，您可以将专家表现看作是一个连续体，从优秀到接近随机。尚托还提出了一些其他相关考虑因素。其中之一是决策支持系统的获取。例如，气象预报员能够做出非常准确的短期预测，并且在很大程度上彼此达成一致，因为他们使用能够预测大气条件的复杂模型。但是，具有相同资历的战略家或经济学家对于明年经济衰退的概率或油价会有不同看法。

Source: James Shanteau, "Why Task Domains (Still) Matter for Understanding Expertise," Journal of Applied Research in Memory and Cognition, Vol. 4, No. 3, September 2015, 169-175.
来源：James Shanteau，“为什么任务领域（仍然）对理解专业知识很重要”，《应用记忆与认知研究杂志》，第 4 卷，第 3 期，2015 年 9 月，169-175 页。

Another consideration is whether experts agree with their prior judgments when presented with similar, or even identical, input over time. For example, wine judges commonly score the same wine differently over separate occasions. This is consistent with what Kahneman calls "noise." Noise occurs when people with the same job come up with different judgments about a specific task or when an individual comes up with different judgments with the same input at different times. Note that noise reflects errors that are all over the place. That is distinct from bias, where errors are wrong in the same way.
另一个考虑因素是专家在随着时间推移呈现类似甚至相同的输入时，是否同意他们之前的判断。例如，葡萄酒评委在不同场合通常会对同一款葡萄酒给出不同的评分。这与卡尼曼所称的“噪音”一致。当从事相同工作的人对特定任务做出不同判断，或者一个人在不同时间对相同输入做出不同判断时，就会出现噪音。请注意，噪音反映了各种错误。这与偏见不同，偏见是指错误以相同方式出现。

The answer to whether pattern recognition is useful for investing is tricky. We can start by assuming that longterm stock market returns combine fundamental company performance (e.g., sales growth, profits, return on investment, payout ratio) and macroeconomic factors (e.g., interest rates, risk premia, economic growth, inflation). But a complicating factor is that the stock market reflects expectations about these inputs. Changes in expectations play a large role in stock price performance, especially in the short to intermediate term.
模式识别对投资是否有用的答案很棘手。我们可以从假设长期股市回报结合基本公司表现（例如销售增长、利润、投资回报率、派息比）和宏观经济因素（例如利率、风险溢价、经济增长、通货膨胀）开始。但一个复杂的因素是股市反映了对这些输入的预期。预期变化在股价表现中起着重要作用，尤其是在短期到中期。

Quantitative investors seek patterns, ideally supported by economic logic, to construct portfolios that aim to generate attractive returns after considering risk. A quantitative model is a decision support system. Quantitative investors seek factors that are associated with excess returns relative to a basic asset pricing model. For example, the stocks that are cheap on multiples of book value or cash flow (value factor) have historically generated higher returns than stocks that are expensive (growth factor). Humans add value by building and updating the model.
量化投资者寻找理想情况下由经济逻辑支持的模式，以构建旨在在考虑风险后产生有吸引力回报的投资组合。量化模型是一个决策支持系统。量化投资者寻找与基本资产定价模型相比产生超额回报的因素。例如，相对于基本资产定价模型，以账面价值或现金流量倍数较低的股票（价值因子）历史上产生的回报比昂贵的股票（成长因子）高。 人类通过构建和更新模型增加价值。

Fundamental investors rely less on decision support systems and more on pattern recognition. Many build portfolios by seeking to select attractive securities based on bottom-up analysis. Specific events, such as the acquisition described in the introduction, often trigger a sense of pattern recognition. Fundamental investors are more vulnerable to seeing patterns that are unreliable or do not exist than quantitative investors because they are less reliant on decision support systems. Indeed, in more uncertain environments people are less likely to use algorithms.
基本投资者更少依赖决策支持系统，更多依赖模式识别。 许多人通过寻求基于自下而上分析选择有吸引力的证券来构建投资组合。特定事件，比如介绍中描述的收购，通常会触发模式识别的感觉。基本投资者比量化投资者更容易看到不可靠或不存在的模式，因为他们更少依赖决策支持系统。事实上，在更不确定的环境中，人们更不太可能使用算法。

We now look at why pattern recognition fails.
我们现在来看一下为什么模式识别失败。

Humans are natural pattern seekers, a quality that likely conferred evolutionary advantage. Patterns have been useful for much of the history of humankind because the environments were relatively stable and cause and effect were evident. Our modern world has created systems where cause and effect are obscure. As a result, well-intentioned human interventions in complex social or natural systems commonly produce unintended consequences. Pattern recognition often fails in complex and evolving environments.
人类是天生的模式寻找者，这一品质很可能带来了进化优势。模式在人类历史的大部分时间里都很有用，因为环境相对稳定，因果关系明显。我们现代世界创造了因果关系模糊的系统。因此，对复杂社会或自然系统的善意干预通常会产生意想不到的后果。在复杂且不断演变的环境中，模式识别经常失败。

Complex adaptive systems are an example of such an environment. "Complex" reflects lots of agents that interact. "Adaptive" means that agents learn and evolve to reflect changes in the environment. And "system" means that the whole that emerges has behaviors that cannot be readily explained by the agents alone. Ant colonies, cities, ecologies, economies, and stock markets are examples of complex adaptive systems.
复杂自适应系统是这种环境的一个例子。“复杂”反映了许多相互作用的代理。“自适应”意味着代理学习和进化以反映环境的变化。而“系统”意味着整体的行为不能仅通过代理来解释。蚁群、城市、生态系统、经济系统和股票市场都是复杂自适应系统的例子。

Properly identifying patterns within these systems is hard because cause and effect is not always clear. These systems also commonly exhibit non-linearity, where a small perturbation leads to a large outcome.
在这些系统中正确识别模式是困难的，因为因果关系并不总是清晰的。这些系统通常还表现出非线性，即小的扰动会导致巨大的结果。

An open letter to Ben Bernanke, then chairman of the Federal Reserve, about the perils of quantitative easing is a good example of illusory links. Quantitative easing, a form of monetary policy, describes when a central bank purchases assets in the open market to lower interest rates and increase the supply of money. Written by prominent economists, strategists, and investors and shared in November 2010, the letter suggested quantitative easing risked "currency debasement and inflation." Neither debasement nor inflation were issues in the years that followed. The pattern of quantitative easing leading to a lower dollar and inflation did not manifest.
致联邦储备委员会主席本·伯南克的一封公开信，讨论量化宽松政策的风险是虚幻联系的一个很好的例子。量化宽松是一种货币政策形式，指的是中央银行在公开市场购买资产以降低利率并增加货币供应。这封信由知名经济学家、策略家和投资者撰写，并于 2010 年 11 月分享，信中指出量化宽松存在“货币贬值和通货膨胀”的风险。 随后的几年中，货币贬值和通货膨胀并未成为问题。量化宽松导致美元贬值和通货膨胀的模式并未出现。

One of the ways that non-linearity shows up in markets is through the loss of diversity. The economist Blake LeBaron is a leader in the field of agent-based modeling. These are models that create agents in silico, provide
市场中非线性表现的一种方式是多样性的丧失。经济学家布雷克·勒巴伦（Blake LeBaron）是代理人建模领域的领军人物。这些模型在硅内创建代理人。
them with decision rules, and let them trade an asset among themselves. The asset has a fair value based on dividends. LeBaron tunes the model to generate asset price movements consistent with empirical reality, including clustered volatility and fat tails. The virtue of this approach is that he can measure the diversity of the decisions the agents make.
用决策规则指导它们，并让它们相互交易资产。该资产的公平价值基于股息。LeBaron 调整模型以生成与实证现实一致的资产价格波动，包括聚类波动和厚尾。这种方法的优点在于他可以衡量代理人所做决策的多样性。

What he finds is that the asset price rises even as the diversity of decision rules declines because the similar trading strategies reinforce the price movement. But at some point the market becomes fragile. At that critical juncture, a small incremental loss of diversity leads to a sharp plunge in the asset price because the buyers are exhausted. The relationship between diversity loss and asset price change is non-linear. Diversity breakdowns fit a pattern but measuring diversity is inherently difficult.
他发现的是，资产价格上涨，即使决策规则的多样性下降，因为相似的交易策略加强了价格的波动。但在某个时刻，市场变得脆弱。在那个关键时刻，多样性的微小损失导致资产价格急剧下跌，因为买家已经筋疲力尽。多样性损失与资产价格变化之间的关系是非线性的。多样性崩溃符合一种模式，但衡量多样性本质上是困难的。

Pattern recognition can also fail because of how our minds love to think in analogies. Steps include selection, mapping, evaluation, and learning. To understand a target topic we commonly start by selecting an analog, usually from memory. We map the target based on the source analog, seeking to make inferences. We evaluate these inferences to judge the similarities and differences between the target and the source. We then learn how the success or failure of the analog applies to the target.
模式识别也可能失败，因为我们的大脑喜欢通过类比来思考。步骤包括选择、映射、评估和学习。 为了理解一个目标主题，我们通常会从记忆中选择一个类比开始。我们根据源类比映射目标，试图进行推理。我们评估这些推理，以判断目标与源之间的相似性和差异。然后我们学习类比的成功或失败如何适用于目标。

Finding the correct analogy is valuable but rare. Pitfalls in the process are the result of breadth and depth. Breadth reflects that we simply have insufficient memory to recall and identify a proper analogy. Depth means the similarities we identify are often superficial and not based on causal factors. The analogy may not work but it creates what Phil Tetlock calls "imaginable scenarios." In studies, participants gain more accurate information when researchers prompt them to consider more than one analog.
找到正确的类比是宝贵的，但却很少见。在这个过程中的陷阱是广度和深度的结果。广度反映了我们仅仅有不足的记忆来回忆和识别一个恰当的类比。深度意味着我们识别的相似之处通常是肤浅的，而不是基于因果因素。类比可能不起作用，但它创造了菲尔·泰特洛克所称的“可想象的情景”。在研究中，当研究人员提示参与者考虑多个类比时，参与者获得更准确的信息。

Because our minds are so good at making analogies, we run the risk of apophenia, defined as "the tendency to perceive a connection or meaningful pattern between unrelated or random things." 39 In the extreme, this can lead to conspiracy theories, superstitions, and false interpretations of randomness.
由于我们的大脑擅长进行类比，我们面临着偏执狂的风险，偏执狂被定义为“倾向于在不相关或随机的事物之间寻找联系或有意义的模式。”39 在极端情况下，这可能导致阴谋论、迷信和对随机性的错误解释。

In fact, there is a module in the left hemisphere of our brain that seeks to create a narrative that links cause and effect. Neuroscientists call this "the interpreter." 40 We are wired to see connections where none exist. The strategy of "frequency matching," where the frequency of choices among alternatives matches the frequency of the reward, is one example. But before discussing how and why adult humans do this, we will learn a lesson from how pigeons decide.
事实上，我们大脑左半球中有一个模块，旨在创造一个将因果联系起来的叙事。神经科学家称之为“解释者”。我们天生就倾向于在不存在联系的地方看到联系。 “频率匹配”策略是一个例子，其中在选择替代方案时的频率与奖励的频率相匹配。但在讨论成年人为何会这样做之前，我们将从鸽子如何做决定中学到一课。

Scientists placed White Carneaux pigeons, the breed that the behaviorist B. F. Skinner had used in his work on conditioning, into an "operant-conditioning chamber" that had two keys they could peck. The researchers set it up so that one of the keys had a higher chance of a food reward than the other. The pigeons figured out which key was better and hit it nearly every time. As a result, they got close to the optimal payoff. Kids under the age of four and rats come to the same strategy.
科学家将白卡诺鸽，即行为主义者 B·F·斯金纳在条件反射研究中使用的品种，放入一个“操作性条件反射室”，里面有两个可以啄击的键。研究人员设置了这样一个情景，其中一个键比另一个更有可能获得食物奖励。鸽子找出了哪个键更好，几乎每次都啄击它。结果，它们接近最佳回报。四岁以下的儿童和老鼠采取了相同的策略。

Adult humans, on the other hand, tend to frequency match. After discovering the probabilities, humans go back and forth between the keys in an attempt to guess the next outcome. They seek a pattern. They select the higher payoff key at a rate that matches the frequency of the payoffs, but still go back and forth between the keys trying to anticipate the rewards. This strategy has a lower payoff than simply selecting the higher payoff key every time.
相反，成年人倾向于频率匹配。在发现概率之后，人类来回在键之间尝试猜测下一个结果。他们寻找模式。他们以与回报频率匹配的速度选择更高回报的键，但仍在键之间来回尝试预测奖励。这种策略的回报低于每次都选择更高回报的键。

Humans frequency match from the time they enter kindergarten on. Here is where the interpreter within the left hemisphere comes in. Neuroscientists studied split-brain patients to figure out where in the brain decisions
人类从进入幼儿园开始就频率匹配。这就是左半球内的解释器发挥作用的地方。神经科学家研究了分裂脑患者，以找出大脑中的决策位置。
happen. These are patients with severe epilepsy that doctors treat by surgically cutting the bundle of nerves between the brain's two hemispheres to relieve the symptoms of epilepsy.
发生。这些是患有严重癫痫病的患者，医生通过手术切断大脑两个半球之间的神经束来缓解癫痫病症状。

The surgery allows scientists to create experiments to assess which parts of the brain deal with various tasks. Researchers worked with these unusual participants to figure out where the inclination to seek patterns resides.
手术使科学家能够创建实验，评估大脑的哪些部分处理各种任务。研究人员与这些不寻常的参与者合作，以找出寻找模式倾向的位置。

The right hemisphere tends to be literal, so it is good at tasks such as facial recognition but bad at making inferences. The left hemisphere is where the circuitry for language largely sits, and it is also great at fabricating narratives to fit facts.
右半球倾向于字面理解，因此擅长于面部识别等任务，但不擅长推理。左半球是语言电路的主要所在，也擅长编造叙述以适应事实。

Researchers found that when presented with a version of the probability guessing experiment, the right hemisphere of split-brain patients maximized just as the pigeons, rats, and little kids did. But when shown the same experiment, the left hemisphere of the patients tried to match the frequency. Your left hemisphere is inclined to see patterns where none exist.
研究人员发现，当向分裂脑患者展示概率猜测实验的一个版本时，右半球像鸽子、老鼠和小孩一样最大化了，但当向患者展示相同实验时，左半球试图匹配频率。您的左半球倾向于在不存在的地方看到模式。

Another reason that pattern recognition fails is that investors often extrapolate. Jason Zweig, a financial journalist, cites an experiment where researchers showed participants a random sequence of squares and circles while monitoring their brain activity with functional magnetic resonance imaging (fMRI). After seeing two squares or circles in a row, the brain of the participants anticipated another of the same symbol.
另一个导致模式识别失败的原因是投资者经常进行外推。金融记者杰森·兹维格（Jason Zweig）引用了一个实验，研究人员在功能性磁共振成像（fMRI）监测下向参与者展示了一个随机的方块和圆圈序列。在看到两个方块或圆圈连续出现后，参与者的大脑会预期下一个符号与之相同。

The neuroscientists who did this work conclude, "The human cognitive system identifies patterns in sequences of events, regardless of whether a pattern truly exists." 45 In this case, the pattern is "what just happened is going to continue happening."
进行这项工作的神经科学家得出结论：“人类认知系统识别事件序列中的模式，无论这种模式是否真实存在。”在这种情况下，模式是“刚刚发生的事情将继续发生”。

Ben Graham, the father of security analysis, shared a cautionary case study about a company called AAA Enterprises. The high-flying stock was first issued to the public in 1969 at per share and immediately shot up to despite flimsy fundamentals. But the stock was grounded shortly thereafter, reaching per share in early 1971, as the firm filed for bankruptcy. Graham wrote, "The speculative public is incorrigible. In financial terms it cannot count beyond 3." 47
本·格雷厄姆是证券分析之父，他分享了一个关于一家名为 AAA 企业的公司的警示案例。这只高飞的股票于 1969 年首次发行给公众，每股 美元，尽管基本面脆弱，但立即飙升至 美元。但不久之后，股票便被迫停飞，到 1971 年初跌至每股 美元，因为公司申请破产。格雷厄姆写道：“投机的公众是无法教育的。在金融术语中，他们无法计数超过 3。” 47

In truth, assuming the future will be similar to the past beats a lot of expert forecasts. But it also introduces the risk of overextrapolation and a failure to recognize regression toward the mean. Financial economists suggest that extrapolation plays an important role in asset pricing, including explaining the momentum factor and the inflation and deflation of bubbles. It also offers insight into why investors anticipate high returns after the market's returns have been high, and low returns after the market's returns have been low.
事实上，假设未来会类似于过去，会超过许多专家的预测。但这也会引入过度外推的风险，以及未能认识到回归均值的风险。金融经济学家建议外推在资产定价中起着重要作用，包括解释动量因子以及泡沫的通胀和通缩。 它还揭示了为什么投资者在市场回报率高后预期高回报，而在市场回报率低后预期低回报。

One key feature of pattern recognition is that it is intuitive. Research in cognitive psychology shows that in some cases when an individual realizes their intuition is misguided, they still act on it rather than correcting their error. This is called "acquiescing" to intuition.
模式识别的一个关键特征是直觉性。认知心理学的研究表明，在某些情况下，当个体意识到他们的直觉是错误的时，他们仍然会依从它，而不是纠正错误。这被称为“顺从直觉”。

For example, in one experiment researchers created a scenario in an American football game where the participant had to choose between punting or going for it on fourth down late in a close game. The analysis showed that going for it had a win probability nine percentage points higher than punting did. Forty percent of the participants had the intuition to punt but understood that the analytics said to go for it. Of that group, 56 percent elected to acquiesce to their intuition and punt anyway.
例如，在一个实验中，研究人员制定了一个场景，即在一场美式橄榄球比赛中，参与者必须在比赛末段选择是选择开球还是继续进攻。分析显示，继续进攻的获胜概率比开球高出九个百分点。百分之四十的参与者本能地选择了开球，但他们明白分析显示应该继续进攻。在这些人中，百分之五十六选择顺从自己的直觉，还是选择开球。

In the case of acquiescence, individuals are aware that pattern recognition does not offer a reliable answer but nevertheless default to it. They fail to correct what they know to be an error.
在默认情况下，个人意识到模式识别并不能提供可靠的答案，但仍然选择默认它。他们未能纠正他们知道是错误的事情。

Acknowledging when pattern recognition is reliable is the first step in trusting its usefulness. Individuals can cultivate pattern recognition in systems that are stable, provide reliable cues, and lend themselves to accurate feedback. Pattern recognition can be alluring but misleading in systems without those traits. The inputs to an investment process can span both systems, so pattern recognition is helpful to fundamental investors in some contexts and unsuitable in others.
承认模式识别可靠时是信任其有用性的第一步。个人可以在稳定、提供可靠线索并能提供准确反馈的系统中培养模式识别能力。在缺乏这些特征的系统中，模式识别可能具有吸引力，但会误导。投资过程的输入可能涵盖两种系统，因此在某些情境下，模式识别对基本投资者有帮助，而在其他情境下则不适用。

Two prerequisites for acquiring intuitive expertise are a stable and linear environment and proper training with inputs that explain what works. Many, if not most, fundamental investors do not meet these basics. They tend to model corporate performance using what psychologists call the "inside view," which focuses on the individual circumstances of a problem and draws heavily on personal understanding. For investors, this is a bottom-up method that considers the firm's specific issues and is guided by the analyst's experience.
获得直觉专业知识的两个前提是稳定和线性的环境以及适当的培训，培训内容解释了有效的方法。许多基本投资者未能满足这些基本要求。他们倾向于使用心理学家所称的“内视”来建模企业绩效，这种方法侧重于问题的个体情况，并且严重依赖个人理解。对于投资者来说，这是一种自下而上的方法，考虑了公司的具体问题，并由分析师的经验指导。

A different approach, called the "outside view," is integral to training for pattern recognition. The outside view considers a problem as an instance of a larger reference class. By knowing the outcomes from the reference class, or the base rates, an investor can make informed, albeit probabilistic, assessments about what will come next. This is the goal of quantitative investors and offers insight into how fundamental investors can hone their ability to recognize patterns.
一种不同的方法，称为“外部视角”，对于模式识别的培训至关重要。外部视角将问题视为更大参考类的一个实例。通过了解参考类的结果，或基础率，投资者可以做出知情的，尽管是概率性的评估，关于接下来会发生什么。这是量化投资者的目标，并揭示了基本投资者如何提高识别模式的能力。

One example is modeling sales growth, which is usually the most important driver of shareholder value. The distribution of sales growth rates tends to be reasonably stable over time, which means it is feasible to place growth expectations in the context of what has happened before. Anticipated growth rates relative to the base rate provide a cue about expectations. Growth that is higher than expected for a company that creates value leads to attractive total shareholder returns. And expected growth versus actual growth offers feedback.
一个例子是建模销售增长，这通常是股东价值的最重要驱动因素。 销售增长率的分布往往随时间相对稳定，这意味着将增长预期放在先前发生的情况下是可行的。相对于基础率的预期增长率提供了关于预期的线索。对于创造价值的公司而言，高于预期的增长会带来有吸引力的股东总回报。而预期增长与实际增长之间的差异则提供反馈。

Sales growth rates show substantial regression toward the mean, which says that results that are far from average tend to be followed by outcomes closer to the average. In practical terms, both high and low past growth rates precede growth rates closer to the average for a population of companies. Sales growth rates and how they regress follow patterns that investors can learn to recognize.
销售增长率显示出明显向平均值回归的趋势，这意味着远离平均水平的结果往往会被接近平均水平的结果所跟随。在实际操作中，无论是高增长率还是低增长率，过去的增长率都会导致公司群体的增长率更接近平均水平。销售增长率及其回归方式遵循一定的模式，投资者可以学会识别这些模式。

The outcomes from M&A are another example of where pattern recognition may be useful, notwithstanding the story in the opening. Historically, most M&A deals have failed to create value for the buyer, as measured by cumulative abnormal stock returns. But there are ways to shade the odds in favor of the buyer, including paying a small premium to acquire the seller, paying for the deal in cash versus stock, and doing deals for businesses that have operations similar to those of the buyer. 55
并购的结果是模式识别可能有用的另一个例子，尽管开头的故事。历史上，大多数并购交易未能为买方创造价值，这是通过累积异常股票回报来衡量的。 但有办法让买方的胜算增加，包括支付小额溢价以收购卖方，用现金而非股票支付交易，以及为与买方类似运营的企业进行交易。55

Observing the distribution of outcomes within a reference class can provide some insight into how difficult it is to predict patterns. For example, since 1984 the distribution of 10 -year sales growth rates for public companies in the U.S. with billion of initial sales follows a distribution that resembles the classic bell curve, with a mean and median around 4.5 percent and a standard deviation of 8.5 percent.
观察参考类别内结果的分布可以帮助我们了解预测模式的难度。例如，自 1984 年以来，美国上市公司初始销售额为 亿美元的 10 年销售增长率分布类似于经典的钟形曲线，平均值和中位数约为 4.5%，标准偏差为 8.5%。

But the distribution of book sales follows a power law, where most of the observations have small outcomes and a few observations have large outcomes. For instance, of the 3 million titles offered by booksellers, only a handful sell more than 1 million copies, about 4,000 new titles sell more than 1,000 in a year, and most sell fewer than Outcomes that follow a power law are generally an indication of a wicked environment, where cause and effect are unclear and pattern recognition is hard.
但是图书销售的分布遵循幂律，大部分观察结果是小规模的，只有少数观察结果是大规模的。例如，在书商提供的 300 万种书籍中，只有少数销售量超过 100 万册，大约有 4,000 种新书每年销售量超过 1,000 册，大多数销售量少于。遵循幂律的结果通常表明了一个复杂的环境，其中因果关系不明确，模式识别困难。

The main challenge in applying base rates effectively is selecting an appropriate reference class. The guidance on how to do so tends to be qualitative. But training intuition, a precursor to useful pattern recognition, almost certainly requires having solid data on the relevant base rate. Cues, causality, and feedback are essential.
在有效应用基础率时面临的主要挑战是选择适当的参考类别。关于如何做到这一点的指导往往是定性的。 但训练直觉，作为有用模式识别的前提，几乎肯定需要对相关基础率有扎实的数据支持。线索、因果关系和反馈是至关重要的。

There is some risk to learning the wrong lessons from an inappropriate reference class, but in our view the bigger risk is a failure to use base rates in the first place. There are a handful of reasons investors do not use base rates. To start, decision makers trust the inside view as it centers on their analysis and experience. This helps explain acquiescence.
从不恰当的参考类别中学到错误教训存在一定风险，但在我们看来，更大的风险是一开始就不使用基础率。投资者不使用基础率的原因有几个。首先，决策者信任内部视角，因为它侧重于他们的分析和经验。这有助于解释顺从。

Individuals also see their situation as unique and do not perceive that examining related instances provides insight. Interestingly, most people are better at recognizing when the outside view applies to others than when it applies to themselves. You can relate to this if you have ever quipped to an acquaintance that their home renovation project will take longer and cost more than they have bargained for.
个人也认为自己的情况独一无二，并不认为研究相关情况能提供洞察。有趣的是，大多数人更擅长意识到外部视角适用于他人，而不是适用于自己。如果你曾经对一个熟人开玩笑说，他们的家庭装修项目将比预期花费更长时间和更多金钱，你可能会有共鸣。

Even in cases when decision makers are willing to use base rates, the data may not be at their fingertips. Few fundamental investors have studied past measures of corporate performance in sufficient detail to prepare their minds to anticipate what might happen in the situation they face. Experience does not offer a simple solution because our memories can capture and retain only a sliver of what has happened.
即使在决策者愿意使用基础率的情况下，数据可能并不是随手可得的。很少有基本投资者对公司绩效的过去措施进行了足够详细的研究，以准备他们的思维来预测他们所面临的情况可能发生的事情。经验并不能提供简单的解决方案，因为我们的记忆只能捕捉和保留发生过的一小部分。

The bottom line is that fundamental investors can train their ability to recognize patterns under the correct conditions. Data that provide cues and causality, as well having a basis for timely and accurate feedback, are fundamental. The efficacy of pattern recognition is context dependent.
底线是，基本投资者可以在正确条件下培养识别模式的能力。提供线索和因果关系的数据，以及及时准确反馈的基础是至关重要的。模式识别的有效性取决于上下文。

Many fundamental investors rely on pattern recognition as part of their decision-making process. They create plausible stories informed by their experience and memory. But it is important to consider how pattern recognition works to understand its applicability.
许多基本投资者依赖模式识别作为决策过程的一部分。他们根据自己的经验和记忆创造合理的故事。但重要的是要考虑模式识别的工作原理，以了解其适用性。

Pattern recognition is more effective in stable environments where cause and effect are clear and participants are trained using timely and accurate feedback. This applies in many domains, including sports, music, and chess. Participants in these areas can develop intuitive expertise, an unconscious sense of recognition that leads to superior performance.
模式识别在稳定环境中更有效，其中因果关系明确，参与者通过及时准确的反馈接受培训。这适用于许多领域，包括体育、音乐和国际象棋。在这些领域的参与者可以培养直觉专业知识，一种无意识的认知感觉，导致卓越表现。

Pattern recognition tends to fail in domains where causality and feedback are limited. But that does not stop decision makers from feeling the sense of pattern recognition. Our mental apparatus allows us to see patterns that truly exist as well as to see them when they do not exist.
模式识别在因果关系和反馈有限的领域往往会失败。但这并不会阻止决策者感受到模式识别的感觉。我们的心智装置使我们能够看到真正存在的模式，也能看到它们不存在时的模式。

Distinguishing between experience and expertise is crucial. All experts have experience but not all with experience are experts. The defining feature of an expert is having a predictive model that works. Ample research shows that expert predictions in social, political, and economic realms are poor. Expert views tend to correlate in realms where expert prediction is effective.
区分经验和专业知识是至关重要的。所有专家都有经验，但并非所有有经验的人都是专家。专家的定义特征是拥有有效的预测模型。大量研究表明，在社会、政治和经济领域，专家的预测往往不准确。专家观点往往在专家预测有效的领域中相关。

This shortcoming is more a reflection of the domain than of the person and underscores the importance of understanding the boundaries of useful prediction. But our minds are keen to go out of bounds, imposing patterns where none exist or acquiescing to our gut reaction even when we know that using explicit analysis can help correct a decision error.
这个缺点更多地反映了领域本身，而不是个人，并强调了理解有用预测边界的重要性。但我们的思维很容易超越界限，强加模式在不存在的地方，或者即使知道使用明确分析可以帮助纠正决策错误，也会顺从我们的直觉反应。

Fundamental investors can build their skill in pattern recognition in certain aspects of the investment process, including assessing fundamental value drivers such as sales growth or judging the stock market's reaction to M&A deals. In both cases, this skill builds on an understanding of base rates and how to use them in prediction.
基本投资者可以在投资过程的某些方面培养他们的模式识别技能，包括评估基本价值驱动因素，如销售增长，或判断股市对并购交易的反应。在这两种情况下，这种技能建立在对基本利率的理解以及如何在预测中使用它们的基础上。

Investors who want to assess their skills at pattern recognition can maintain a journal and document their intuitions. Done properly, this allows for the measurement of calibration, or how well probabilistic forecasts match the frequency of outcomes. Over time, such an accurate self-assessment can help reveal where and when pattern recognition is accurate and adds value.
希望评估自己模式识别能力的投资者可以保持一本日记，记录他们的直觉。如果做得当，这可以用来衡量校准度，即概率预测与结果频率匹配的程度。随着时间的推移，这样准确的自我评估可以帮助揭示模式识别何时何地准确且有价值。

Anthony Ramirez, "ConAgra Agrees to Purchase of Beatrice for $1.34 Billion," New York Times, June 8, 1990.
安东尼·拉米雷斯，“康尼格拉同意以 13.4 亿美元收购比阿特丽斯”，《纽约时报》，1990 年 6 月 8 日。

George P. Baker, "Beatrice: A Study in the Creation and Destruction of Value," Journal of Finance, Vol. 47, No. 3, July 1992, 1081-1119.
George P. Baker，“Beatrice: A Study in the Creation and Destruction of Value”，《金融学杂志》，第 47 卷，第 3 期，1992 年 7 月，1081-1119。

Glenn Yago, Junk Bonds: How High Yield Securities Restructured Corporate America (Oxford: Oxford University Press, 1991), 148.
格伦·亚戈，《垃圾债券：高收益证券如何重组美国企业》（牛津：牛津大学出版社，1991 年），148 页。

At the time of this deal, there were two ways to account for an acquisition: pooling and purchase. To simplify greatly, with pooling the balance sheets of the buyer and seller were added together and there was no effect on earnings. With a purchase, any payment above book value was recorded as goodwill, and amortized over a period up to 40 years. In this case there was a negative effect on earnings. In 2001, the Financial Accounting Standards Board (FASB) got rid of pooling as well as the amortization of goodwill. Today companies must only do a periodic check to verify that the carrying value of goodwill is proper and take a write-down if the value is impaired. See Abraham J. Briloff, "Cannibalizing the Transcendent Margin: Reflections on Conglomeration, LBOs, Recapitalizations and Other Manifestations of Corporate Mania," Financial Analysts Journal, Vol. 44, No. 3, May-June 1988, 74-80.
在这笔交易时，有两种方法来处理收购：合并和购买。简化来说，合并是指买方和卖方的资产负债表相加，对收益没有影响。而购买则是指超过账面价值的任何支付都被记录为商誉，并在最长 40 年的期间内摊销。在这种情况下，对收益有负面影响。2001 年，财务会计准则委员会（FASB）取消了合并以及商誉摊销。今天，公司只需定期检查以确保商誉的账面价值正确，并在价值受损时进行减值。参见亚伯拉罕·J·布里洛夫，《吞噬超越边际：对企业集团化、LBO、资本重组及其他公司狂热表现的反思》，《金融分析师杂志》，第 44 卷，第 3 期，1988 年 5-6 月，74-80 页。

Alan Sloan, "KKR and the Big Leveraged Buyout End of an Age," Washington Post, June 19, 1990.
艾伦·斯隆，《KKR 和大型杠杆收购时代的终结》，《华盛顿邮报》，1990 年 6 月 19 日。

Shortly after the deal, Conagra changed its internal earnings measure to reflect that goodwill is a non-cash and non-economic charge. From the company's 1994 Form 10-K: "During fiscal 1993, we improved our objectives by incorporating a concept called 'cash earnings'-net earnings plus goodwill amortization. Businesses run on cash. The principal source of internally generated cash is net earnings before depreciation of fixed assets and amortization of goodwill. Cash from depreciation is generally needed for replenishment to help maintain a going concern. On the other hand, goodwill represents valuable non-depreciating brands and distribution systems, primarily those we acquired with Beatrice Company in fiscal year 1991. We invest and incur expense throughout the year to maintain and enhance the value of these brands and distribution systems. Consequently, goodwill amortization is not a true economic cash cost. It, along with net earnings, is a source of decision cash-cash available to invest in ConAgra's growth and pay dividends." (Emphasis added.)
交易完成后不久，康尼格拉改变了其内部盈利衡量标准，以反映商誉是一项非现金和非经济性支出。根据公司 1994 年的 10-K 表格：“在 1993 财政年度，我们通过引入一个名为‘现金收益’的概念来改进我们的目标-净收益加上商誉摊销。企业以现金运作。内部产生现金的主要来源是固定资产折旧和商誉摊销前的净收益。折旧产生的现金通常用于补充资金，以帮助维持企业的持续经营。另一方面，商誉代表有价值的不折旧品牌和分销系统，主要是我们在 1991 财政年度与比阿特丽斯公司收购的那些。我们全年投资并发生费用，以维护和增强这些品牌和分销系统的价值。因此，商誉摊销不是真正的经济现金成本。它与净收益一起，是决策现金的来源-可用于投资康尼格拉的增长和支付股息。”（强调添加）

AV Ventures Communications Team, "Best Practices in Patter Recognition," Alumni Ventures, November 9, 2021.
AV Ventures 通讯团队，“模式识别的最佳实践”，校友风投，2021 年 11 月 9 日。

8 See www.merriam-webster.com/dictionary/pattern (the seventh definition) and www.merriam-webster.com/ dictionary/recognize.
查看 www.merriam-webster.com/dictionary/pattern（第七个定义）和 www.merriam-webster.com/dictionary/recognize。

9 Michael Grant and Fredrik Nilsson, Intuitive Expertise and Financial Decision-Making (Abingdon, UK: Routledge, 2023).
9 迈克尔·格兰特（Michael Grant）和弗雷德里克·尼尔森（Fredrik Nilsson），《直觉专业知识与金融决策》（英国阿宾登：劳特利奇出版社，2023 年）。

Hebert A. Simon, "What Is an 'Explanation' of Behavior?" Psychological Science, Vol. 3, No. 3, May 1992, .
西蒙（Hebert A. Simon），“行为的‘解释’是什么？”《心理科学》，第 3 卷，第 3 期，1992 年 5 月。

K. A. Ericsson and A. C. Lehmann, "Expert and Exceptional Performance: Evidence of Maximal Adaptation to Task Constraints," Annual Review of Psychology, Vol. 47, No. 1, February 1996, 273-305.
K. A. Ericsson 和 A. C. Lehmann，"Expert and Exceptional Performance: Evidence of Maximal Adaptation to Task Constraints," 《心理学年度评论》，第 47 卷，第 1 期，1996 年 2 月，273-305。

12 Michelene T. H. Chi, Robert Glaser, and Marshall Farr, eds., The Nature of Expertise (Hillsdale, NJ: Lawrence Erlbaum Associates, 1988), xvii-xx and Erik Dane, Kevin W. Rockmann, Michael G. Pratt, "When Should I Trust My Gut? Linking Domain Expertise to Intuitive Decision-Making Effectiveness," Organizational Behavior and Human Decision Processes, Vol. 119, No. 2, November 2012, 187-194.
12 Michelene T. H. Chi，Robert Glaser 和 Marshall Farr，编，专家的本质（Hillsdale，NJ：劳伦斯·埃尔鲁姆协会，1988 年），xvii-xx 和 Erik Dane，Kevin W. Rockmann，Michael G. Pratt，“我何时应该相信直觉？将领域专业知识与直觉决策效果联系起来”，组织行为和人类决策过程，第 119 卷，第 2 期，2012 年 11 月，187-194。

William Poundstone, Priceless: The Myth of Fair Value (and How to Take Advantage of It) (New York: Hill and Wang, 2010), 199. Also, Emre Soyer and Robin H. Hogarth, "Fooled by Experience," Harvard Business Review, Vol. 93, No. 5, May 2015, 72-77.
William Poundstone，《无价：公平价值的神话（以及如何利用它）》，希尔与旺出版社，2010 年，第 199 页。另外，Emre Soyer 和 Robin H. Hogarth，《被经验愚弄》，《哈佛商业评论》，第 93 卷，第 5 期，2015 年 5 月，第 72-77 页。

14 Gregory B. Northcraft and Margaret A. Neale, "Experts, Amateurs, and Real Estate: An Anchoring-andAdjustment Perspective on Property Pricing Decisions," Organizational Behavior and Human Decision Processes, Vol. 39, No. 1, February 1987, 84-97.
14 Gregory B. Northcraft 和 Margaret A. Neale，“Experts, Amateurs, and Real Estate: An Anchoring-andAdjustment Perspective on Property Pricing Decisions,” Organizational Behavior and Human Decision Processes，Vol. 39, No. 1，1987 年 2 月，84-97。

Philip E. Tetlock, Expert Political Judgment: How Good Is It? How Can We Know? (Princeton, NJ: Princeton University Press, 2005).
菲利普·E·泰特洛克，《专家政治判断：有多准确？我们如何知道？》（普林斯顿，新泽西州：普林斯顿大学出版社，2005 年）。

16 Ibid., 40. 16 同前，40。
Robert A. Olsen, "Professional Investors as Naturalistic Decision Makers: Evidence and Market Implications," Journal of Psychology and Financial Markets, Vol. 3, No. 3, 2002, 161-167.
Robert A. Olsen，“专业投资者作为自然决策者：证据和市场影响”，《心理学与金融市场杂志》，第 3 卷，第 3 期，2002 年，161-167。

18 Thomas Gilovich, Dale Griffin, and Daniel Kahneman, eds., Heuristics and Biases: The Psychology of Intuitive Judgment (Cambridge, UK: Cambridge University Press, 2002).
18 Thomas Gilovich, Dale Griffin, and Daniel Kahneman, 编辑，启发与偏见：直觉判断的心理学（剑桥，英国：剑桥大学出版社，2002 年）。

For examples of where it works, see Gary Klein, Intuition at Work: Why Developing Your Gut Instincts Will Make You Better at What You Do (New York: Currency/Doubleday, 2003). For examples of where it fails, see Daniel Kahneman and Amos Tversky, "Intuitive Prediction: Biases and Corrective Procedures," Decision Research Technical Report PTR-1042-77-6, 1977.
要了解它起作用的例子，请参阅 Gary Klein 的《Intuition at Work: Why Developing Your Gut Instincts Will Make You Better at What You Do》（纽约：Currency/Doubleday，2003）。要了解它失败的例子，请参阅 Daniel Kahneman 和 Amos Tversky 的《Intuitive Prediction: Biases and Corrective Procedures》，“Decision Research Technical Report PTR-1042-77-6”，1977 年。

Gary Klein, Sources of Power: How People Make Decisions (Cambridge, MA: MIT Press, 1999) and Gary Klein, Intuition at Work: Why Developing Your Gut Instincts Will Make You Better at What You Do (New York: Currency/Doubleday, 2003).
Gary Klein，《力量的源泉：人们如何做决策》（剑桥，麻省理工学院出版社，1999 年）和 Gary Klein，《直觉在工作中：为什么培养你的直觉会让你在工作中表现更出色》（纽约：Currency/Doubleday，2003 年）。

Daniel Kahneman, Thinking, Fast and Slow (New York: Farrar, Straus and Giroux, 2011).
丹尼尔·卡尼曼，《思考，快与慢》（纽约：法拉尔、斯特劳斯和吉鲁克斯，2011 年）。

22 Daniel Kahneman and Gary Klein, "Conditions for Intuitive Expertise: A Failure to Disagree," American Psychologist, Vol. 64, No. 6, September 2009, 515-526 and "Adversarial Collaboration: An EDGE Lecture by Daniel Kahneman," see www.edge.org/adversarial-collaboration-daniel-kahneman.
22 丹尼尔·卡尼曼和加里·克莱因，《直觉专业知识的条件：不同意的失败》，《美国心理学家》，第 64 卷，第 6 期，2009 年 9 月，515-526 页，《对抗性合作：丹尼尔·卡尼曼的 EDGE 讲座》，请参阅 www.edge.org/adversarial-collaboration-daniel-kahneman。

Fernand Gobet and Herbert A. Simon, "Expert Chess Memory: Revisiting the Chunking Hypothesis," Memory, Vol. 6, No. 3, 1998, 225-255.
Fernand Gobet 和 Herbert A. Simon，“Expert Chess Memory: Revisiting the Chunking Hypothesis”，《Memory》，第 6 卷，第 3 期，1998 年，225-255。

Robin M. Hogarth, Educating Intuition (Chicago: University of Chicago Press, 2001) and Robin M. Hogarth, Tomás Lejarraga, and Emre Soyer, "The Two Settings of Kind and Wicked Learning Environments," Current Directions in Psychological Science, Vol. 24, No. 5, October 2015, 379-385.
Robin M. Hogarth, 教育直觉（芝加哥：芝加哥大学出版社，2001 年）和 Robin M. Hogarth，Tomás Lejarraga 和 Emre Soyer，“善良和邪恶学习环境的两种设置”，《心理科学当前方向》，第 24 卷，第 5 期，2015 年 10 月，379-385。

25 Hillel J. Einhorn, "Expert Judgment: Some Necessary Conditions and an Example," Journal of Applied Psychology, Vol. 59, No. 5, October 1974, 562-571.
25 Hillel J. Einhorn，“Expert Judgment: Some Necessary Conditions and an Example”，《应用心理学杂志》，第 59 卷，第 5 期，1974 年 10 月，562-571 页。

Mark Greer, "Directional Accuracy Tests of Long-Term Interest Rate Forecasts," International Journal of Forecasting, Vo. 19, No. 2, April-June 2003, 291-298.
Mark Greer，“长期利率预测的方向准确性测试”，《国际预测期刊》，第 19 卷，第 2 期，2003 年 4-6 月，291-298。

27 Jeff Sommer, "Forget Stock Market Forecasts. They're Less Than Worthless," New York Times, December 23, 2019 and Michael Boutros, Itzhak Ben-David, John R. Graham, Campbell R. Harvey, and John W. Payne, "The Persistence of Miscalibration," NBER Working Paper 28010, October 2020.
27 Jeff Sommer，“忘记股市预测。它们不值一提，”《纽约时报》，2019 年 12 月 23 日，迈克尔·布特罗斯，伊扎克·本-大卫，约翰·R·格雷厄姆，坎贝尔·R·哈维和约翰·W·佩恩，“误差的持续性”，NBER 工作论文 28010，2020 年 10 月。

Robert T. Hodgson, "An Examination of Judge Reliability at a Major U.S. Wine Competition, Journal of Wine Economics, Vol. 3, No. 2, Fall 2008, 105-113.
Robert T. Hodgson，“美国一项重要葡萄酒比赛中法官可靠性的研究”，《葡萄酒经济学杂志》，第 3 卷，第 2 期，2008 年秋季，105-113。

Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein, Noise: A Flaw in Human Judgment (New York: Little, Brown Spark, 2021).
丹尼尔·卡尼曼（Daniel Kahneman）、奥利维尔·西博尼（Olivier Sibony）和卡斯·R·桑斯坦（Cass R. Sunstein），《噪音：人类判断中的缺陷》（纽约：Little, Brown Spark，2021 年）。

Evan Nesterak, “A Conversation with Daniel Kahneman About 'Noise'," Behavioral Scientist, May 24, 2021.
Evan Nesterak，“与丹尼尔·卡尼曼关于'噪音'的对话”，《行为科学家》，2021 年 5 月 24 日。

Eugene F. Fama and Kenneth R. French, "The Cross-Section of Expected Stock Returns," Journal of Finance, Vol. 47, No. 2, June 1992, 427-465.
尤金·法玛（Eugene F. Fama）和肯尼斯·R·弗伦奇（Kenneth R. French），《预期股票收益的横截面》，《金融学杂志》，第 47 卷，第 2 期，1992 年 6 月，427-465。

At the end of the day, the returns of fundamental and systematic equity funds are similar after adjusting for volatility and other factor exposures. See Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, and Otto Van Hemert, "Man vs. Machine: Comparing Fundamental and Systematic Hedge Fund Performance," Journal of Portfolio Management, Vol. 43, No. 4, Summer 2017, 55-69.
在一天结束时，调整波动性和其他因素暴露后，基本和系统性股票基金的回报相似。请参阅 Campbell R. Harvey、Sandy Rattray、Andrew Sinclair 和 Otto Van Hemert 的文章《人类 vs. 机器：比较基本和系统性对冲基金绩效》，《投资组合管理杂志》，第 43 卷，第 4 期，2017 年夏季，55-69 页。

Berkeley J. Dietvorst, and Soaham Bharti, "People Reject Algorithms in Uncertain Decision Domains Because They Have Diminishing Sensitivity to Forecasting Error," Psychological Science, Vol. 31, No. 10, October 2020, 1302-1314.
伯克利 J.迪特沃斯特和索哈姆·巴尔蒂，“人们在不确定决策领域拒绝算法，因为他们对预测错误的敏感性逐渐降低”，《心理科学》，第 31 卷，第 10 期，2020 年 10 月，1302-1314。

As a slight diversion, the workings of complex adaptive systems are part of the debate about the existence of free will. See Robert M. Sapolsky, Determined: A Science of Life Without Free Will (New York: Penguin Press, 2023), 154-202.
作为一个轻微的偏离，复杂自适应系统的运作是关于自由意志存在的辩论的一部分。参见罗伯特·M·萨波尔斯基（Robert M. Sapolsky）著，《Determined: A Science of Life Without Free Will》（纽约：企鹅出版社，2023 年），第 154-202 页。

35 "Open Letter to Ben Bernanke," November 15, 2010. See www.wsj.com/articles/BL-REB-12460.
35 "致本•伯南克的公开信"，2010 年 11 月 15 日。请参阅 www.wsj.com/articles/BL-REB-12460。

Blake LeBaron, "Financial Market Efficiency in a Coevolutionary Environment," Proceedings of the Workshop on Simulation of Social Agents: Architectures and Institutions, Argonne National Laboratory and University of Chicago, October 2000, Argonne 2001, 33 51. LeBaron writes, "During the run-up to a crash, population diversity falls. Agents begin to use very similar trading strategies as their common good performance begins to selfreinforce. This makes the population very brittle, in that a small reduction in the demand for shares could have a strong destabilizing impact on the market. The economic mechanism here is clear. Traders have a hard time
Blake LeBaron，“金融市场效率在共同进化环境中的研究”，《社会代理模拟：结构与制度研讨会论文集》，阿贡国家实验室和芝加哥大学，2000 年 10 月，阿贡 2001 年，33-51 页。LeBaron 写道，“在崩盘前，人口多样性下降。代理商开始使用非常相似的交易策略，因为它们的共同良好表现开始自我强化。这使得人口非常脆弱，因为对股票需求的轻微减少可能对市场产生强烈的破坏性影响。这里的经济机制很明显。交易商很难。
finding anyone to sell to in a falling market since everyone else is following very similar strategies. In the Walrasian setup used here, this forces the price to drop by a large magnitude to clear the market. The population homogeneity translates into a reduction in market liquidity."
在一个下跌的市场中找到任何人进行销售，因为其他人都在遵循非常相似的策略。在这里使用的 Walrasian 设置中，这迫使价格大幅下跌以清理市场。人口的同质性导致市场流动性减少。

Keith J. Holyoak and Paul Thagard, Mental Leaps: Analogy in Creative Thought (Cambridge, MA: MIT Press, 1995), 15.
Keith J. Holyoak 和 Paul Thagard，《Mental Leaps: Analogy in Creative Thought》（剑桥，麻省：麻省理工学院出版社，1995 年），第 15 页。

Dan Lovallo, Carmina Clarke, and Colin Camerer, "Robust Analogizing and the Outside View: Two Empirical Tests of Case-Based Decision Making," Strategic Management Journal, Vol. 33, No. 5, May 2012, 496-512.
Dan Lovallo、Carmina Clarke 和 Colin Camerer，“Robust Analogizing and the Outside View: Two Empirical Tests of Case-Based Decision Making”，《战略管理杂志》，第 33 卷，第 5 期，2012 年 5 月，496-512。

39 See https://www.merriam-webster.com/dictionary/apophenia.
39 请参阅 https://www.merriam-webster.com/dictionary/apophenia。

Michael S. Gazzaniga, Tales from Both Sides of the Brain: A Life in Neuroscience (New York: Ecco, 2015), 150-153.
迈克尔·S·加扎尼加，《大脑两面的故事：神经科学中的一生》（纽约：Ecco，2015），150-153。

41 John M. Hinson and J. E. R. Staddon, "Matching, Maximizing, and Hill-Climbing," Journal of the Experimental Analysis of Behavior, Vol. 40, No. 3, November 1983, 321-331 and Peter L. Derks and Marianne I. Paclisanu, "Simple Strategies in Binary Prediction by Children and Adults," Journal of Experimental Psychology, Vol. 73, No. 2, February 1967, 278-285.
41 John M. Hinson 和 J. E. R. Staddon，“匹配、最大化和爬山”，《行为实验分析杂志》，第 40 卷，第 3 期，1983 年 11 月，321-331 和 Peter L. Derks 和 Marianne I. Paclisanu，“儿童和成人在二元预测中的简单策略”，《实验心理学杂志》，第 73 卷，第 2 期，1967 年 2 月，278-285。

42 In a coin tossing game that was biased toward heads (60 percent), nearly one-half of the participants bet on tails more than five times in the game and the likelihood of betting on tails increased after a string of heads. See Victor Haghani and Richard Dewey, "Rational Decision Making under Uncertainty: Observed Betting Patterns on a Biased Coin," Journal of Portfolio Management, Vol. 43, No. 3, Spring 2017, 2-8. In another experiment, participants learned about marble draws ( 30 green and 10 red) and then asked to guess the color of additional draws to win money. This group also frequency matched. See Derek J. Koehler and Greta James, "Probability Matching in Choice under Uncertainty: Intuition versus Deliberation," Cognition, Vol. 113, No. 1, October 2009, 123-127.
在一个向正面倾斜的硬币抛掷游戏中（60％），将近一半的参与者在游戏中押注尾巴超过五次，而在连续出现正面后，押注尾巴的可能性增加。参见 Victor Haghani 和 Richard Dewey，“不确定情况下的理性决策：偏向硬币上的观察到的押注模式”，《投资组合管理杂志》，第 43 卷，第 3 期，2017 年春季，2-8 页。在另一个实验中，参与者了解了大理石抽取（30 个绿色和 10 个红色），然后被要求猜测额外抽取的颜色以赢取金钱。这个组也进行了频率匹配。参见 Derek J. Koehler 和 Greta James，“不确定情况下选择中的概率匹配：直觉与深思”，《认知》，第 113 卷，第 1 期，2009 年 10 月，123-127 页。

43 There's an interesting twist in this work. When the researchers showed the patients words, the right hemisphere maximized and the left hemisphere frequency matched. But when they showed faces, which are processed in the right hemisphere, the results were reversed and right hemisphere frequency matched and the left hemisphere maximized. See Michael S. Gazzaniga, Tales from Both Sides of the Brain: A Life in Neuroscience (New York: Ecco, 2015), 294-296.
在这项工作中有一个有趣的转折。当研究人员向患者展示单词时，右半球最大化，左半球频率匹配。但当他们展示在右半球中处理的面孔时，结果却相反，右半球频率匹配，左半球最大化。参见迈克尔·S·加扎尼加（Michael S. Gazzaniga），《大脑两侧的故事：神经科学中的一生》（纽约：Ecco，2015 年），294-296 页。

Jason Zweig, Your Money and Your Brain: How the New Science of Neuroeconomics Can Help Make You Rich (New York: Simon & Schuster, 2007), 69-70.
Jason Zweig，《你的金钱和你的大脑：神经经济学的新科学如何帮助你致富》（纽约：西蒙与舒斯特，2007 年），69-70 页。

Scott A. Huettel, Peter B. Mack, and Gregory McCarthy, "Perceiving Patterns in Random Series: Dynamic Processing of Sequence in Prefrontal Cortex," Nature Neuroscience, Vol. 5, No. 5, May 2002, 485-490.
Scott A. Huettel, Peter B. Mack, and Gregory McCarthy，“在随机序列中感知模式：前额叶皮层中序列的动态处理”，《自然神经科学》，第 5 卷，第 5 期，2002 年 5 月，485-490。

There were 780 initial public offerings in 1969, the most of any year since 1960. See Roger G. Ibbotson, Jody L. Sindelar, and Jay R. Ritter, "The Market's Problems with the Pricing of Initial Public Offerings," Journal of Applied Corporate Finance, Vol. 7, No. 1, Spring 1994, 66-74.
1969 年有 780 家首次公开发行，是自 1960 年以来数量最多的一年。参见 Roger G. Ibbotson、Jody L. Sindelar 和 Jay R. Ritter 的文章《市场对首次公开发行定价的问题》，发表于 1994 年春季《应用公司金融杂志》第 7 卷第 1 期，66-74 页。

Benjamin Graham, The Intelligent Investor: A Book of Practical Counsel, Fourth Revised Edition (New York: Harper & Row, 1973), 245.
本杰明·格雷厄姆，《聪明的投资者：实用建议之书》，第四版修订版（纽约：哈珀罗，1973 年），245 页。

48 Nicholas Barberis, "Psychology-Based Models of Asset Prices and Trading Volume," in Handbook of Behavioral Economics-Foundations and Applications, Vol. 1, B. Douglas Bernheim, Stefano DellaVigna and David Laibson, eds. (Amsterdam: North-Holland, 2018), 79-175 and Nicholas Barberis, Robin Greenwood, Lawrence Jin, and Andrei Shleifer, "Extrapolation and Bubbles," Journal of Financial Economics, Vol. 129, No. 2, August 2018, 203-227.
48 Nicholas Barberis，“基于心理学的资产价格和交易量模型”，载于《行为经济学手册-基础与应用》，第 1 卷，B. Douglas Bernheim，Stefano DellaVigna 和 David Laibson 主编（阿姆斯特丹：北荷兰，2018 年），79-175 页，以及 Nicholas Barberis，Robin Greenwood，Lawrence Jin 和 Andrei Shleifer，“外推和泡沫”，《金融经济学杂志》，第 129 卷，第 2 期，2018 年 8 月，203-227 页。

Robin Greenwood and Andrei Shleifer, "Expectations of Returns and Expected
罗宾·格林伍德（Robin Greenwood）和安德烈·什莱弗（Andrei Shleifer），《收益预期和预期

Returns," Review of Financial Studies, Vol. 27, No. 3, March 2014, 714-746.
回报，“金融研究评论”，第 27 卷，第 3 期，2014 年 3 月，714-746。

50 Jane L. Risen, "Believing What We Do Not Believe: Acquiescence to Superstitious Beliefs and Other Powerful Intuitions," Psychological Review, Vol. 123, No. 2, March 2016, 182-207 and Jane L. Risen, "Acquiescing to Intuition: Believing What We Know Isn't So," Social and Personality Psychology Compass, Vol. 11, No. 11, November 2017, e12358.
50 Jane L. Risen，“相信我们不相信的事情：对迷信信念和其他强大直觉的顺从”，《心理评论》，第 123 卷，第 2 期，2016 年 3 月，182-207 和 Jane L. Risen，“顺从直觉：相信我们知道不是真的事情”，《社会与个性心理学指南》，第 11 卷，第 11 期，2017 年 11 月，e12358。

51 The details do not matter for those who are not familiar with American football. Note only that conventional wisdom and past practice (intuition) would advocate punting and analytics would support going for it.
对于不熟悉美式橄榄球的人来说，细节并不重要。请注意，传统智慧和过去的做法（直觉）会主张踢球，而分析则支持进攻。

52 Daniel K. Walco and Jane L. Risen, "The Empirical Case for Acquiescing to Intuition," Psychological Science, Vol. 28, No. 12, December 2017, 1807-1820.
52 Daniel K. Walco 和 Jane L. Risen，“The Empirical Case for Acquiescing to Intuition”，Psychological Science，第 28 卷，第 12 期，2017 年 12 月，1807-1820。
Etienne Theising, Dominik Wied, Daniel Ziggel, "Reference Class Selection in Similarity-Based Forecasting of Corporate Sales Growth, Journal of Forecasting, Vol. 42, No. 5, August 2023, 1069-1085.
Etienne Theising, Dominik Wied, Daniel Ziggel，“基于相似性的企业销售增长预测中的参考类别选择，预测杂志，第 42 卷，第 5 期，2023 年 8 月，1069-1085。

Mark Sirower and Jeff Weirens, The Synergy Solution: How Companies Win the Mergers and Acquisitions Game (Boston, MA: Harvard Business Review Press, 2022), 7.
Mark Sirower 和 Jeff Weirens，《协同解决方案：公司如何赢得并购游戏》（波士顿，马萨诸塞州：哈佛商业评论出版社，2022 年），第 7 页。

55 This is an example of "similarity-based forecasting," where placing different weights on instances within the reference class can sharpen forecasting accuracy. For example, this might benefit an assessment of an M&A deal. See Lovallo, Clarke, and Camerer, "Robust Analogizing and the Outside View."
这是“基于相似性的预测”的一个例子，在这种情况下，在参考类别中对实例赋予不同的权重可以提高预测准确性。例如，这可能有利于评估一项并购交易。请参阅 Lovallo、Clarke 和 Camerer 的《强大的类比和外部视角》。

Michael J. Mauboussin and Dan Callahan, "The Impact of Intangibles on Base Rates," Consilient Observer: Counterpoint Global Insights, June 23, 2021.
迈克尔·J·莫布森和丹·卡拉汉，《无形资产对基础率的影响》，《共识观察者：对冲全球洞察》，2021 年 6 月 23 日。

Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman, "Power-Law Distributions in Empirical Data," Society for Industrial and Applied Mathematics Review, Vol. 51, No. 4, November 2009, 661-703.
Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman，“实证数据中的幂律分布”，《工业和应用数学评论》，第 51 卷，第 4 期，2009 年 11 月，661-703。

Xindi Wang, Burcu Yucesoy, Onur Varol, Tina Eliassi-Rad, and Albert-László Barabási, "Success in Books: Predicting Book Sales Before Publication," EPJ Data Science, Vol. 8, Article No. 31, October 2019. Movies have similar outcomes. See Arthur DeVany, Hollywood Economics: How Extreme Uncertainty Shapes the Film Industry (New York: Routledge, 2004).
辛迪·王，布尔丘·尤塞索伊，奥纳尔·瓦罗尔，蒂娜·伊利亚西-拉德和阿尔伯特-拉斯洛·巴拉巴西，“图书成功：预测出版前的图书销量”，EPJ 数据科学，第 8 卷，第 31 篇文章，2019 年 10 月。电影有类似的结果。参见亚瑟·德瓦尼，《好莱坞经济学：极端不确定性如何塑造电影行业》（纽约：劳特利奇，2004 年）。

Kahneman and Tversky, "Intuitive Prediction." Some guidance has been offered in a legal context. See Edward K. Cheng, "A Practical Solution to the Reference Class Problem," Columbia Law Review, Vol. 109, No. 8, December 2009, 2081-2105.
康曼和特维斯基，《直觉预测》。在法律背景下提供了一些指导。参见 Edward K. Cheng，《参考类问题的实用解决方案》，哥伦比亚法律评论，第 109 卷，第 8 期，2009 年 12 月，2081-2105 页。

Bent Flyvbjerg and Dan Gardner, How Big Things Get Done: The Surprising Factors That Determine the Fate of Every Project, from Home Renovations to Space Exploration and Everything In Between (New York: Crown Currency, 2023).
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David G. Myers, Intuition: Its Powers and Perils (New Haven, CT: Yale University Press, 2002).
大卫·G·迈尔斯，《直觉：其力量与危险》（康涅狄克州纽黑文：耶鲁大学出版社，2002 年）。

Arthur, W. Brian, "Foundations of Complexity Economics," Nature Reviews Physics, Vol. 3, No. 2, February 2021, 136-145.
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Baker, George P., "Beatrice: A Study in the Creation and Destruction of Value," Journal of Finance, Vol. 47, No. 3, July 1992, 1081-1119.
贝克，乔治 P.，“比阿特丽斯：价值创造与破坏研究”，《金融学杂志》，第 47 卷，第 3 期，1992 年 7 月，1081-1119 页。

Barberis, Nicholas, "Psychology-Based Models of Asset Prices and Trading Volume," in Handbook of Behavioral Economics-Foundations and Applications, Vol. 1, B. Douglas Bernheim, Stefano DellaVigna and David Laibson, eds. (Amsterdam: North-Holland, 2018), 79-175.
巴贝里斯，尼古拉斯，“基于心理学的资产价格和交易量模型”，收录于《行为经济学手册-基础与应用》，第 1 卷，主编伯恩海姆、德拉维尼亚和莱布森（阿姆斯特丹：北荷兰，2018 年），79-175 页。

Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer, "Extrapolation and Bubbles," Journal of Financial Economics, Vol. 129, No. 2, August 2018, 203-227.
Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer, “Extrapolation and Bubbles,” Journal of Financial Economics, Vol. 129, No. 2, August 2018, 203-227.

Beatrice Company, Form 10-Q, August 31, 1990.
比阿特丽斯公司，表格 10-Q，1990 年 8 月 31 日。

Bilalić, Merim, Anna Conci, Mario Graf, and Nemanja Vaci, "The Neural Underpinnings of Expertise in Games," in The Science of Expertise: Behavioral, Neural, and Genetic Approaches to Complex Skill, David Z. Hambrick, Guillermo Campitelli, and Brooke N. Macnamara, eds. (New York: Routledge, 2018), 182-199.
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Bonabeau, Eric, “Don't Trust Your Gut," Harvard Business Review, Vol. 81, No. 5, May 2003, 116-123.
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Boutros, Michael, Itzhak Ben-David, John R. Graham, Campbell R. Harvey, and John W. Payne, "The Persistence of Miscalibration," NBER Working Paper 28010, October 2020.
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Briloff, Abraham J., "Cannibalizing the Transcendent Margin: Reflections on Conglomeration, LBOs, Recapitalizations and Other Manifestations of Corporate Mania," Financial Analysts Journal, Vol. 44, No. 3, MayJune 1988, 74-80.
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Cheng, Edward K., "A Practical Solution to the Reference Class Problem," Columbia Law Review, Vol. 109, No. 8, December 2009, 2081-2105.
程，Edward K.，“参考类问题的实用解决方案”，哥伦比亚法律评论，第 109 卷，第 8 期，2009 年 12 月，2081-2105。

Chi, Michelene T. H., Robert Glaser, and Marshall Farr, eds., The Nature of Expertise (Hillsdale, NJ: Lawrence Erlbaum Associates, 1988), xvii-xx.
齐，米歇琳·T·H.，罗伯特·格莱泽和马歇尔·法尔，编，《专业知识的本质》（新泽西州希尔斯代尔：劳伦斯·埃尔鲁姆协会，1988 年），第 xvii-xx 页。

Clauset, Aaron, Cosma Rohilla Shalizi, and M. E. J. Newman, "Power-Law Distributions in Empirical Data," Society for Industrial and Applied Mathematics Review, Vol. 51, No. 4, November 2009, 661-703.
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Dane, Erik, Kevin W. Rockmann, Michael G. Pratt, "When Should I Trust My Gut? Linking Domain Expertise to Intuitive Decision-Making Effectiveness," Organizational Behavior and Human Decision Processes, Vol. 119, No. 2, November 2012, 187-194.
丹尼，埃里克，凯文·W·洛克曼，迈克尔·G·普拉特，“我何时应该相信直觉？将领域专业知识与直觉决策效果联系起来”，《组织行为与人类决策过程》，第 119 卷，第 2 期，2012 年 11 月，187-194 页。

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德瓦尼（DeVany, Arthur）, 《好莱坞经济学：极端不确定性如何塑造电影产业》（Hollywood Economics: How Extreme Uncertainty Shapes the Film Industry）（纽约：Routledge, 2004）。

Dietvorst, Berkeley J., and Soaham Bharti, "People Reject Algorithms in Uncertain Decision Domains Because They Have Diminishing Sensitivity to Forecasting Error," Psychological Science, Vol. 31, No. 10, October 2020, 1302-1314.
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Desai, Hemang, and Prem C. Jain, "An Analysis of the Recommendations of the 'Superstar' Money Managers at Barron's Annual Roundtable," Journal of Finance, Vol. 50, No. 4, September 1995, 1257-1273.
Desai, Hemang, 和 Prem C. Jain, "An Analysis of the Recommendations of the 'Superstar' Money Managers at Barron's Annual Roundtable," Journal of Finance, Vol. 50, No. 4, September 1995, 1257-1273.

Dijkstra, Koen A., Joop Van Der Pligt, and Gerben A. Van Kleef, "Deliberation Versus Intuition: Decomposing the Role of Expertise in Judgment and Decision Making," Journal of Behavioral Decision Making, Vol. 26, No. 3, July 2013, 285-294.
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Fama, Eugene F., and Kenneth R. French, "The Cross-Section of Expected Stock Returns," Journal of Finance, Vol. 47, No. 2, June 1992, 427-465.
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The views and opinions and/or analysis expressed are those of the author as of the date of preparation of this material and are subject to change at any time due to market or economic conditions and may not necessarily come to pass. Furthermore, the views will not be updated or otherwise revised to reflect information that subsequently becomes available or circumstances existing, or changes occurring, after the date of publication. The views expressed do not reflect the opinions of all investment personnel at Morgan Stanley Investment Management (MSIM) and its subsidiaries and affiliates (collectively "the Firm"), and may not be reflected in all the strategies and products that the Firm offers.
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Forecasts and/or estimates provided herein are subject to change and may not actually come to pass. Information regarding expected market returns and market outlooks is based on the research, analysis and opinions of the authors or the investment team. These conclusions are speculative in nature, may not come to pass and are not intended to predict the future performance of any specific strategy or product the Firm offers. Future results may differ significantly depending on factors such as changes in securities or financial markets or general economic conditions.
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Past performance is no guarantee of future results. This material has been prepared on the basis of publicly available information, internally developed data and other third-party sources believed to be reliable. However, no assurances are provided regarding the reliability of such information and the Firm has not sought to independently verify information taken from public and third-party sources. The views expressed in the books and articles referenced in this whitepaper are not necessarily endorsed by the Firm.
过往表现并不预示未来结果。本材料基于公开信息、内部开发数据和其他第三方来源准备而成，这些来源被认为是可靠的。然而，并未就此类信息的可靠性提供保证，公司也未寻求独立验证从公开和第三方来源获取的信息。在本白皮书引用的书籍和文章中表达的观点并不一定得到公司的认可。

This material is a general communications which is not impartial and has been prepared solely for information and educational purposes and does not constitute an offer or a recommendation to buy or sell any particular security or to adopt any specific investment strategy. The material contained herein has not been based on a consideration of any individual client circumstances and is not investment advice, nor should it be construed in any way as tax, accounting, legal or regulatory advice. To that end, investors should seek independent legal and financial advice, including advice as to tax consequences, before making any investment decision.
这份材料是一份一般性的通讯，不是公正的，并且仅供信息和教育目的而准备，不构成购买或出售任何特定证券或采用任何特定投资策略的要约或建议。此处包含的材料并未基于任何个别客户情况的考虑，也不构成投资建议，也不应以任何方式解释为税务、会计、法律或监管建议。因此，投资者在做出任何投资决定之前应寻求独立的法律和财务建议，包括税务后果的建议。

Charts and graphs provided herein are for illustrative purposes only. Any securities referenced herein are solely for illustrative purposes only and should not be construed as a recommendation for investment.
本文提供的图表仅供参考。本文提及的任何证券仅供参考，不应被视为投资建议。

This material is not a product of Morgan Stanley's Research Department and should not be regarded as a research material or a recommendation.
此材料并非摩根士丹利研究部门的产品，不应视为研究材料或建议。

The Firm has not authorised financial intermediaries to use and to distribute this material, unless such use and distribution is made in accordance with applicable law and regulation. Additionally, financial intermediaries are required to satisfy themselves that the information in this material is appropriate for any person to whom they provide this material in view of that person's circumstances and purpose. The Firm shall not be liable for, and accepts no liability for, the use or misuse of this material by any such financial intermediary.
公司未授权金融中介使用和分发本材料，除非此类使用和分发符合适用法律和法规。此外，金融中介需要确保本材料中的信息适合他们向任何人提供本材料的情况和目的。公司对任何金融中介对本材料的使用或滥用不承担责任，也不承担任何责任。

The whole or any part of this work may not be directly or indirectly reproduced, copied, modified, used to create a derivative work, performed, displayed, published, posted, licensed, framed, distributed or transmitted or any of its contents disclosed to third parties without MSIM's express written consent. This work may not be linked to unless such hyperlink is for personal and non-commercial use. All information contained herein is proprietary and is protected under copyright and other applicable law.
本作品的全部或部分内容未经 MSIM 明确书面同意，不得直接或间接复制、修改、用于创作衍生作品、执行、展示、发布、张贴、许可、框架、分发或传输，也不得将其任何内容透露给第三方。除非超链接用于个人和非商业用途，否则不得链接到本作品。此处包含的所有信息均为专有信息，受版权和其他适用法律保护。

Eaton Vance is part of Morgan Stanley Investment Management. Morgan Stanley Investment Management is the asset management division of Morgan Stanley.
伊顿万通是摩根士丹利投资管理的一部分。摩根士丹利投资管理是摩根士丹利的资产管理部门。

This material may be translated into other languages. Where such a translation is made this English version remains definitive. If there are any discrepancies between the English version and any version of this material in another language, the English version shall prevail.
本材料可能被翻译成其他语言。如果进行了这样的翻译，英文版本仍然是决定性的。如果英文版本与其他语言版本的任何版本之间存在任何不一致，应以英文版本为准。

This communication is only intended for and will only be distributed to persons resident in jurisdictions where such distribution or availability would not be contrary to local laws or regulations.
本通讯仅适用于并仅将分发给居住在不会违反当地法律或法规的司法管辖区的人。

MSIM, the asset management division of Morgan Stanley (NYSE: MS), and its affiliates have arrangements in place to market each other's products and services. Each MSIM affiliate is regulated as appropriate in the jurisdiction it operates. MSIM's affiliates are: Eaton Vance Management (International) Limited, Eaton Vance Advisers International Ltd, Calvert Research and Management, Eaton Vance Management, Parametric Portfolio Associates LLC, and Atlanta Capital Management LLC.
摩根士丹利（NYSE：MS）的资产管理部门 MSIM 及其关联公司已经建立安排，以推广彼此的产品和服务。每个 MSIM 关联公司在其运营的司法管辖区受到适当监管。MSIM 的关联公司包括：伊顿范斯管理（国际）有限公司、伊顿范斯顾问国际有限公司、卡尔弗特研究与管理、伊顿范斯管理、Parametric Portfolio Associates LLC 和亚特兰大资本管理有限责任公司。

This material has been issued by any one or more of the following entities:
本材料已由以下一个或多个实体发布：

This material is for Professional Clients/Accredited Investors only.
本材料仅供专业客户/合格投资者使用。

In the EU, MSIM and Eaton Vance materials are issued by MSIM Fund Management (Ireland) Limited (“FMIL"). FMIL is regulated by the Central Bank of Ireland and is incorporated in Ireland as a private company limited by shares with company registration number 616661 and has its registered address at 24-26 City Quay, Dublin 2, DO2 NY19, Ireland.
在欧盟，MSIM 和伊顿范斯材料由 MSIM 基金管理（爱尔兰）有限公司（“FMIL”）发行。 FMIL 受爱尔兰中央银行监管，作为一家私人股份有限公司在爱尔兰注册，公司注册号码为 616661，注册地址位于爱尔兰都柏林 2 区 City Quay 24-26 号，邮编 D02 NY19。

Outside the EU, MSIM materials are issued by Morgan Stanley Investment Management Limited (MSIM Ltd) is authorised and regulated by the Financial Conduct Authority. Registered in England. Registered No. 1981121. Registered Office: 25 Cabot Square, Canary Wharf, London E14 4QA.
在欧盟之外，MSIM 材料由根斯坦利投资管理有限公司（MSIM Ltd）发行，受英国金融行为监管局授权和监管。在英格兰注册，注册号码 1981121。注册办公地址：伦敦金丝雀码头卡伯特广场 25 号。

In Switzerland, MSIM materials are issued by Morgan Stanley & Co. International plc, London (Zurich Branch) Authorised and regulated by the Eidgenössische Finanzmarktaufsicht ("FINMA"). Registered Office: Beethovenstrasse 33, 8002 Zurich, Switzerland.
在瑞士，MSIM 材料由根斯坦利国际有限公司伦敦分公司（苏黎世分公司）发行，受瑞士金融市场监管局（"FINMA"）授权和监管。注册办公地址：瑞士苏黎世 Beethovenstrasse 33 号，邮编 8002。

Outside the US and EU, Eaton Vance materials are issued by Eaton Vance Management (International) Limited ("EVMI") 125 Old Broad Street, London, EC2N 1AR, UK, which is authorised and regulated in the United Kingdom by the Financial Conduct Authority.
在美国和欧盟之外，伊顿范斯材料由伊顿范斯管理（国际）有限公司（“EVMI”）发布，地址为英国伦敦 Old Broad Street 125 号，邮编 EC2N 1AR，受英国金融行为监管局监管和授权。

Italy: MSIM FMIL (Milan Branch), (Sede Secondaria di Milano) Palazzo Serbelloni Corso Venezia, 1620121 Milano, Italy. The Netherlands: MSIM FMIL (Amsterdam Branch), Rembrandt Tower, 11th Floor Amstelplein 1 1096HA, Netherlands. France: MSIM FMIL (Paris Branch), 61 rue de Monceau 75008 Paris, France. Spain: MSIM FMIL (Madrid Branch), Calle Serrano 55, 28006, Madrid, Spain. Germany: MSIM FMIL Frankfurt Branch, Große Gallusstraße 18, 60312 Frankfurt am Main, Germany (Gattung: Zweigniederlassung (FDI) gem. § 53b KWG). Denmark: MSIM FMIL (Copenhagen Branch), Gorrissen Federspiel, Axel Towers, Axeltorv2, 1609 Copenhagen V, Denmark.
意大利：MSIM FMIL（米兰分行），（米兰分部）Palazzo Serbelloni Corso Venezia，1620121 Milano，意大利。荷兰：MSIM FMIL（阿姆斯特丹分行），Rembrandt Tower，11 楼 Amstelplein 1，1096HA，荷兰。法国：MSIM FMIL（巴黎分行），61 rue de Monceau 75008 巴黎，法国。西班牙：MSIM FMIL（马德里分行），Calle Serrano 55，28006，马德里，西班牙。德国：MSIM FMIL 法兰克福分行，Große Gallusstraße 18，60312 法兰克福，德国（类型：分支机构（FDI）根据 KWG 第 53b 条）。丹麦：MSIM FMIL（哥本哈根分行），Gorrissen Federspiel，Axel Towers，Axeltorv2，1609 哥本哈根 V，丹麦。

Dubai: MSIM Ltd (Representative Office, Unit Precinct 3-7th Floor-Unit 701 and 702, Level 7, Gate Precinct Building 3, Dubai International Financial Centre, Dubai, 506501, United Arab Emirates. Telephone: +97 (0)14 709 7158).
迪拜：MSIM 有限公司（代表处，单元 3-7 楼-701 和 702 单元，第 7 层，门区大厦 3 号，迪拜国际金融中心，迪拜，506501，阿拉伯联合酋长国。电话：+97（0）14 709 7158）。

This document is distributed in the Dubai International Financial Centre by Morgan Stanley Investment Management Limited (Representative Office), an entity regulated by the Dubai Financial Services Authority ("DFSA"). It is intended for use by professional clients and market counterparties only. This document is not intended for distribution to retail clients, and retail clients should not act upon the information contained in this document.
本文件由根据迪拜金融服务管理局（“DFSA”）监管的摩根士丹利投资管理有限公司（代表处）在迪拜国际金融中心分发。仅供专业客户和市场交易对手使用。本文件不适用于零售客户，零售客户不应根据本文件中包含的信息采取行动。

Hong Kong: This material is disseminated by Morgan Stanley Asia Limited for use in Hong Kong and shall only be made available to "professional investors" as defined under the Securities and Futures Ordinance of Hong Kong (Cap 571). The contents of this material have not been reviewed nor approved by any regulatory authority including the Securities and Futures Commission in Hong Kong. Accordingly, save where an exemption is available under the relevant law, this material shall not be issued, circulated, distributed, directed at, or made available to, the public in Hong Kong. Singapore: This material is disseminated by Morgan Stanley Investment Management Company and should not be considered to be the subject of an invitation for subscription or purchase, whether directly or indirectly, to the public or any member of the public in Singapore other than (i) to an institutional investor under section 304 of the Securities and Futures Act, Chapter 289 of Singapore ("SFA"); (ii) to a "relevant person" (which includes an accredited investor) pursuant to section 305 of the SFA, and such distribution is in accordance with the conditions specified in section 305 of the SFA; or (iii) otherwise pursuant to, and in accordance with the conditions of, any other applicable provision of the SFA. This publication has not been reviewed by the Monetary Authority of Singapore. Australia: This material is provided by Morgan Stanley Investment Management (Australia) Pty Ltd ABN 22122040037, AFSL No. 314182 and its affiliates and does not constitute an offer of interests. Morgan Stanley Investment Management (Australia) Pty Limited arranges for MSIM affiliates to provide financial services to Australian wholesale clients. Interests will only be offered in circumstances under which no disclosure is required under the Corporations Act 2001 (Cth) (the "Corporations Act"). Any offer of interests will not purport to be an offer of interests in circumstances under which disclosure is required under the Corporations Act and will only be made to persons who qualify as a "wholesale client" (as defined in the Corporations Act). This material will not be lodged with the Australian Securities and Investments Commission.
香港：本材料由摩根士丹利亚洲有限公司在香港发布，仅供根据香港证券及期货条例（第 571 章）定义的“专业投资者”使用。本材料的内容未经任何监管机构审查或批准，包括香港证券及期货事务监察委员会。因此，除非根据相关法律有豁免规定，否则本材料不得在香港发行、传播、分发、指向或提供给公众。 新加坡：此材料由摩根士丹利投资管理公司传播，不应被视为直接或间接向新加坡公众或任何新加坡公众成员发出订阅或购买邀请的对象，除非（i）根据新加坡《证券及期货法》第 289 章第 304 条向机构投资者发出；（ii）根据新加坡《证券及期货法》第 289 章第 305 条向“相关人士”（包括合格投资者）发出，并且此分发符合第 305 条规定的条件；或（iii）根据新加坡《证券及期货法》的任何其他适用规定发出，并符合该法规定的条件。此出版物未经新加坡金融管理局审查。澳大利亚：此材料由摩根士丹利投资管理（澳大利亚）私人有限公司提供，ABN 22122040037，AFSL 编号 314182 及其关联公司，并不构成利益提供。摩根士丹利投资管理（澳大利亚）私人有限公司安排 MSIM 关联公司向澳大利亚批发客户提供金融服务。 利益只会在不需要根据 2001 年《公司法》（"公司法"）披露的情况下提供。 利益的任何提供都不会被视为在根据《公司法》需要披露的情况下提供利益，并且只会提供给符合《公司法》中"批发客户"（定义见于《公司法》）资格的人。 这份材料不会提交给澳大利亚证券和投资委员会。

This material may not be circulated or distributed, whether directly or indirectly, to persons in Japan other than to (i) a professional investor as defined in Article 2 of the Financial Instruments and Exchange Act ("FIEA") or (ii) otherwise pursuant to, and in accordance with the conditions of, any other allocable provision of the FIEA. This material is disseminated in Japan by Morgan Stanley Investment Management (Japan) Co., Ltd., Registered No. 410 (Director of Kanto Local Finance Bureau (Financial Instruments Firms)), Membership: the Japan Securities Dealers Association, The Investment Trusts Association, Japan, the Japan Investment Advisers Association and the Type II Financial Instruments Firms Association.
本材料不得直接或间接地传播或分发给日本境内的个人，除非是（i）根据《金融商品交易法》第 2 条定义的专业投资者，或者（ii）根据《金融商品交易法》的其他可分配规定，并符合相关条件。本材料由摩根士丹利投资管理（日本）有限公司在日本传播，注册编号 410（关东地方财务局（金融工具公司）主管），会员：日本证券经纪商协会、日本投资信托协会、日本投资顾问协会和第二类金融工具公司协会。