MIT SLOAN SCHOOL OF MANAGEMENT FINANCE PROFESSOR Andrew Lo traces his interest in economics to a seemingly unlikely source: science fiction author Isaac Asimov. As a student at New York’s Bronx High School of Science in the mid-’70s, Lo was a fan of Asimov’s Foundation series, whose central character, Hari Seldon, develops a fictional field of study called psychohistory that combines history, psychology and statistics to predict the actions of a large group of people. “The idea that you couldn’t tell what an individual was going to do but that you could say with more certainty what a population of individuals might do struck me as being quite plausible,” explains Lo, who graduated in three years from Yale University with a BA in economics in 1980 and earned his Ph.D. from Harvard University four years later at the age of 24. “That’s exactly what the field of financial economics is all about.”
Todayacademics like Loare drawn to finance because it deals with very practical real-world problems such as what an asset is worth or where to invest capital. For those with a strong quantitative bent — Lo, for example, originally intended to major in biochemistry, math and physics at Yale — finance is especially attractive as a laboratory in which they can develop and test their
理论。但对于财务的大部分历史，只要有市场，已经存在，严肃的经济学家在很大程度上忽略了这个领域。它并没有开始吸引理论者的注意，直到20世纪60年代和70年代。
“Prior to then finance had been pretty much the purview of business schools, which were pretty nontheoretical places with lots of institutional material and rules of thumb,” saysWilliam Sharpe78，斯坦福大学经过漫长的职业教学金融后，现在退休。“那么经济学家侵入金融，询问有关人们以某种方式做事并遵循某些规则的问题。”
Sharpe was among a band of young economists with revolutionary ideas for introducing uncertainty into finance and using computers to crunch data and run regression analyses. In 1964 he published a groundbreaking paper on the资本资产定价模型那which reduced to a simple formula the relationship between risk and return that most market participants already intuitively knew: To achieve higher returns, investors need to take on greater risks. CAPM introduced alpha (excess return) and beta (a measure of market risk) to the investment lexicon and became one of the pillars of modern, or “neoclassical,” finance. It also earned Sharpe the 1990 Nobel Prize in economic sciences. That year he shared the award with Harry Markowitz, the father ofModern Portfolio Theory那and Merton Miller, best known for his work on corporate finance.
The decision by the Nobel committee to recognize Markowitz, Miller and Sharpe brought legitimacy to the field of finance. It was also a key endorsement of the major assumptions underpinning modern financial theory — that markets are efficient and that investors have rational expectations and can process information quickly and accurately.The Efficient Market Hypothesis那introduced in 1970 by University of Chicago Booth School of Business finance professor Eugene Fama, and CAPM suggest that it is difficult, if not impossible, for active investors to beat the market.
Not surprisingly, the asset management industry has embraced Modern Portfolio Theory, which is basically a user’s guide on how to construct an “efficient,” or well-diversified, portfolio, maximizing the investment return for a given level of risk. Fund managers, however — apart from Vanguard Group and a few other companies that have built their businesses on indexing — have not embraced the notion that markets are efficient. For support, they can turn to the field of behavioral finance, which Santa Clara University finance professor Hersh Shefrin defines as “the application of psychology to the study of financial decision making and financial markets.”
Behavioral finance traces its roots to the research of Israeli psychologists Daniel Kahneman and Amos Tversky, who through a series of experiments starting in the late ’60s showed that people are not always rational when making decisions and make mistakes in judgment because of heuristics and cognitive biases. By the 1980s reports of anomalies — including unexplained investor and market behavior as a result of the effects of loss aversion, mental accounting, overconfidence and overreaction — began appearing in professional journals, by economists such as Chicago’s Richard Thaler (then at Cornell University) and Yale’s Robert Shiller, calling into question the dogma of rational behavior.
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“It was [British economist] Alfred Marshall who said over 100 years ago that economics is not an exact science,” Shiller, 66, explains. “The problem is, it’s the study of people. There’s some mysterious extra that comes with human will and intention. But it’s very hard to reduce to a formula.”
From the outset neoclassical economists rejected the behavioral school. “There’s no behavioral theory; it’s all just inefficient markets,” says Fama, 73. “It’s a big blanket, not a theory of its own. Unless there’s a coherent theory that can be subjected to tests, there’s nothing to replace [the Efficient Market Hypothesis] with.”
The neoclassical finance camp has had a strong supporter in Boston University finance professor Zvi Bodie, co-author with Alan Marcus and Alex Kane of Investments, the textbook used by most U.S. MBA programs. Although the book, now in its ninth printing, devotes one chapter to behavioral finance, Bodie is clearly not a believer. “Shiller and all those people are basically wrong,” he says. “They know it but won’t admit it.”
The debate — some would say battle — between the neoclassical finance school and behavioral theorists has yet to be settled. That’s because one critical factor has not been addressed by either camp, posits Paul Woolley, senior fellow at the London School of Economics. In The Future of Finance, published by the LSE in 2010, Woolley calls for “a science-based, unified theory of finance . . . that retains as much as possible of the existing analytical framework and at the same time produces credible explanations and predictions.”
He is looking for a solution in the principal-agent relationship.
Woolley以及他的同事Dimitri Vayanos是在麻省理工学院和斯坦福商学院教授的LSE教授，相信资本市场繁荣和崩溃已经抵消了高效的市场假设。“市场效率高的想法是40岁，”伍德利说。“这不再可信。我们提供另类范式。“具体而言，Woolley和Vayanos断言私人，个人投资者未设定价格，因为他们几乎将所有的投资决策委托给金融中介机构或代理商。代表团创建了一个机构问题。
After 25 years as partner, then chairman, of asset manager GMO’s London office — which he opened — Woolley in 2007 established the Paul Woolley Center for the Study of Capital Market Dysfunctionality at the LSE, naming Vayanos as director. Through this institution Woolley is offering a new theory of finance that he hopes will produce credible explanations and predictions for market behavior. “Two things happen if you introduce the principal-agent problem,” says Woolley, 73. “One, you get asset mispricing, as markets are momentum-driven. Two, the agents are in a position to capture excess returns that should go to the asset owners.”
Momentum — the tendency of a stock or market to continue in the same direction it has recently been moving — is incompatible with efficient markets, argues Woolley, and has been difficult to explain, even by the likes of Fama. In 1993, Fama and colleague Kenneth French (now a finance professor at Dartmouth College’s Tuck School of Business)introduced a “three-factor model“解释与高效市场假设相矛盾的势头和价值影响。但Vayanos对此有不同的占据。他目前正在研究一个新的资产定价模型，其中包括个人如何选择其资产经理以及货币如何从经理流向经理。正如Vayanos所看到的那样的问题是，投资者对他们的经理有不完全了解。因此，当投资基金表现不佳时，投资者 - 无法判断经理是否无能或审慎地避免价格过高的股票 - 拿走他们的资金并将其交给经理，并将其交给现代的经理。以这种方式，优惠管理者持有的过高的证券被驱动得更高。Vayanos表示，这种错误的不论是由投资者的非理性或愚蠢造成的，而是他们对管理资金的代理商的不完美知识。
“这些流程可以解释势头和价值效应，”他补充道。“我们的代理视图表示，也许一切都可以在一个完全理性的世界中理解。”
麻省理工学院在他的职业生涯中花了一遍职业生涯，试图解释他在研究生院的理性理论和他之后他读过的行为金融文学之间的理性理论之间的冲突。其中的部分时间是宾夕法尼亚州沃顿省沃顿省沃顿省沃顿省沃顿省的助理融资教授，他和同胞A. Craig Mackinlay教授看着每次被记录的市场异常，以了解他们是否有某种实证解释。他们找不到任何东西。“我尝试了各种各样的方式解释结果，但最终我意识到如果我们理解有效的市场假设有局限性，我就会变得更加容易，”罗说。
With that in mind, he began reading through the literature on evolutionary biology, neuroscience and psychology to explore what those limitations might be. The result is what呼吁自适应市场假设据称，这表明，这是应用进化 - 竞争，适应和自然选择的原则 - 金融决策。作为LO解释，金融市场是对特定环境挑战的适应性反应的一个例子。“如果我们将最大化我们的生存机会，拥有金融市场比没有金融市场的效果好多，”他说。“这是进化的一部分。”
The Adaptive Markets Hypothesis attempts to reconcile the contradictions between efficient-markets theory and behavioral finance by focusing on how people adapt to a changing environment, using both logical reasoning (which takes place in the prefrontal cortex of the brain) and more-primitive responses such as the fight-or-flight impulse when someone is threatened. (The latter is characterized by a series of almost instantaneous physiological changes, including the release of glucose into the bloodstream, increase in blood flow and acceleration of reflexes.) Understanding the interaction between both kinds of decision-making mechanisms is critical: “The behavioral biases that psychologists and behavioral economists have documented are simply adaptations that have been taken out of their evolutionary context,” Lo wrote in a recent article for the财务分析师杂志。“Fight-or-flight is an extremely effective decision-making system in a street fight but is potentially disastrous in a financial crisis.”
根据Lo,在电信市场效率的变化me based on “the relative proportion of market participants who are making decisions with their prefrontal cortexes versus their more instinctive faculties.” Similarly, the trade-off between risk and reward changes over time. During periods of fear like the 2008 financial crisis, investors rush into safer assets, which has “the effect of reducing the average return on risky assets and increasing the average return on safer ones, exactly the opposite of what rational finance predicts,” Lo writes. According to the CAPM, investors should be rewarded, not punished, for taking on more risk.
Lo no longer sounds like a financial economist; his speech is punctuated with words from evolutionary biology, like “survival,” “species” and “adaptation.” He concedes: “It’s getting harder and harder for me to talk to my colleagues because I have a different way of thinking about it. The way I think about it actually has greater explanatory power, as opposed to people maximizing expected utility, the income shock and where they substitute for other assets. All those theories are wonderful in terms of the precision of the forecasts they produce. The problem is that those forecasts are routinely violated.”
当涉及到无穷无尽的追求ledge, it’s best to attack from all angles. That’s why Andrew Caplin, professor of economics at New York University and a self-described man of many hats, has eschewed affixing himself to any one field of economic research. He sees value in collecting and analyzing data from varied sources. The mountainous stacks of papers occupying the desk and bookshelves in his Washington Square Park office indicate as much.
“我喜欢去行动和思想的地方有效，”伦敦出生的经济学家说，他在美国贸易竞争以来他收到了博士学位。与1983年耶鲁耶鲁的区别。
这种对学术界的方法已经带领Caplin，56，to conduct research on varying topics中国国际广播电台,从生命周期消费美国住房sis. Since the early 2000s he has spent much of his time on a relatively new field of study he believes is a treasure trove of data: neuroeconomics, which amalgamates economics, psychology and neuroscience to explore the underpinnings of why and how people make the choices they do.
Caplin并不孤单。其他着名机构的研究人员，包括加州大学，伦敦大学学院和苏黎世大学，都被神经经济学吸引了。该纪律是行为金融的自然进展，第一个要研究认知偏见和资产定价之间关系的领域。虽然行为金融旨在调和决策背后的心理和经济学，但Caplin表示它没有提供完整的解释。
“The delight about behavioral is that it never has to say it’s wrong,” he explains, echoing criticisms from the neoclassical crowd. “It’s about the other guys being wrong. You can’t win in the long run this way. What’s right? Is there anything you can rule out? Their class of anomalies is infinite.”
At the core of a neoclassical finance model like the CAPM is the idea of balancing risk and return. Behavioralists point out that because humans are not perfect, mistakes are made in this measurement. Although economists have been able to document how biases such as overconfidence or herding may cause a person to miscalculate, they have struggled to come up with empirical evidence to explain why. The addition of neuroscience to the fold allows researchers literally to take a peek inside the brain to view risk and return in real time as investors make choices.
理解决策的钥匙之一是神经递质多巴胺。神经递质是大脑的邮政工人，在连接器官数十亿神经元的突触上发送电气信息。多巴胺可以在大脑的几个区域中找到，在奖励途径增强行为中发挥着重要作用，这使得满足或愉悦的行为。从生理立场，多巴胺的释放是响应投资决策的预期回报提供了评估人们学习和价值信息的有用数据。建成良好的神经科学实验不仅可以发现受试者错误地体现了投资期权的风险，它也可以针对在制作中选择之前，期间和之后的大脑的面积。
The promise of neuroscience brought Caplin together with Paul Glimcher, head of纽约的神经经济中心中心。虽然Caplin是象征着许多帽子的人，但闪光实际上在他的办公室里留下了三个：两个棒球帽分别印在“经济学家”和“心理学家”的话语和一个充满资本“N，”神经科学家的硬帽子。“在他的职业生涯中，玉米威尼斯神经科学助理教授被作为生理学家和数学心理学家培训的神经科学担任者得出结论，进一步促进他对决策的神经系统工作，他需要更充实的经济理论掌握在它背后的经济理论。所以他去了街对阵纽约的经济学部门，开始上海研究生课程，慢慢地将自己称为经济学家。
50岁的凝聚器正在寻找组织神经活动的原则;Caplin正在寻找衡量选择行为的新方法。七年前，他们开始一起教导神经科学和经济学研讨会。Caplin看到了个人在微观经济学层面的选择在很大程度上在世界的宏观视图中被忽视。“经济学家的根本问题是我们对我们的数据非常难以捉摸，”他解释道。“我们不明白为什么我们出错，而且它是因为数据。储蓄理论是世界各国的行为理论。好吧，我们没有看到世界各国。“
事务所Caplin和Glimcher combined their expertise to come up with an expanded understanding of dopamine, building on the work of University of Cambridge neuroscience professor Wolfram Schultz and others. In the 1990s, Schultz, then at the University of Fribourg in Switzerland, conducted an experiment in which he recorded the neural activity of thirsty monkeys that received drops of juice, preceded by a tone, at irregular intervals. He found that the dopamine neurons fired when the monkeys heard the tone, not when they tasted the juice. “These findings led to the hypothesis that dopamine was encoding the difference between ‘experienced’ and ‘predicted’ reward, or a ‘reward prediction error,’ ” Caplin and Glimcher在2010年文章中写道Quarterly Journal of Economics。The article, which was coauthored by then–NYU colleagues Mark Dean and Robb Rutledge, was based on experiments using functional magnetic resonance imaging (fMRI) to record people’s brain activity when given lottery choices. By measuring dopamine release, they were able to determine whether prizes were more or less rewarding than expected, providing further support for “the conclusion that reward prediction error-based learning of value occurs in the human brain.”
从neuronucleu帕萨迪纳市2800英里远s that is NYU, researchers at Caltech have also taken a keen interest in the neurological underpinnings of economic decision making. What started as a collaboration between two like-minded professors has become one of the most notable neuroeconomic research efforts in the world. The two,Colin Camerer，行为经济学教授，和Peter Bossaerts.那a professor of economics, management and finance, were able to sneak neuroeconomics into a relatively narrow Caltech curriculum and proceed from there.
A preeminent U.S. research university, Caltech attracts top thinkers. It has produced 31 Nobel Prize winners, almost all in physics, chemistry and physiology or medicine, and has five laureates currently in residence, out of a full-time professorial faculty of 297. With fewer than 1,000 undergrads and a 3-to-1 student-to-teacher ratio, the lowest of any research university in the U.S., Caltech may not seem the obvious choice to join the prominent ranks of a social-science-minded discipline like neuroeconomics. But just as in sports or an orchestra, “talented intense people want to be around talented intense people,” says Camerer, who had earned an MBA in finance and a Ph.D. in decision theory from the University of Chicago by the age of 22. Caltech has six professors working on neuroeconomic research; Antonio Rangel, the most recent addition, heads up the neuroeconomics laboratory.
Camerer于1994年加入CALTECH于1994年在芝加哥大学，沃顿和西北大学的凯洛格管理学院教学，并专注于未来十年的更好部分的行为博弈论。当Caltech安装了第一个FMRI机器时，他于2003年对2003年的神经经济学感兴趣。在Camerer的实验之一中，参与者被联系到脑扫描仪，并在人为市场中的50小时股票交易期间观察到。受试者使用镜片内部照明的交易屏幕或在扫描仪内观看的屏幕。在另一个研究中，货币赌博实验，凸轮使用脑电图（EEG），测量脑电活动，研究称为杏仁症的脑部的杏仁形面积，已知对损失厌恶很重要。
“如果你真的想认真研究情绪，你必须在生物学上衡量它，”凸轮，52。“某种数据的新来源，无论是实验还是实验加神经科学都会有所帮助。”
CALTECH的BOSSAERTS也在新鲜数据中看到了价值。“我利用实验控制获得了更好地了解金融问题的基本问题，”比利时出生的52岁的人，他们在现在被称为安特卫普大学和博士学位的应用经济学博士学位。在加利福尼亚大学的管理层中，洛杉矶。“这从系统级别[市场]向下走向个人。”
Bossaerts’ interest in market experiments led him to explore empirical tests on theories, including the CAPM, to see which ones held up, and how. The CAPM “lends itself very well to laboratory experiment because it has only one period horizon,” he explains. In these experiments Bossaerts created minimarkets for about 30 participants, who were given an allocation of stocks and cash, as well as expected dividends and possible payoffs, and were provided with a simplified, user-friendly trading system. Bossaerts noticed that while the Markowitz theory behind the model did not hold up, the CAPM on the whole did. “That was our first indication that there is something in this theory that’s right, and there is something completely wrong,” he says.
The Caltech professor’s interest in neuroscience stems from what he sees as the problem with economics in general and finance in particular: They try to explain behavior without understanding the neurological processes that lead to decision making. He also doesn’t like how both neoclassical and behavioral economists view emotions, blaming them for bad decisions and insisting that people need to be emotionless to make good ones. “Just from the point of view of evolutionary biology, this made no sense,” says Bossaerts, echoing the themes in Lo’s Adaptive Markets Hypothesis. “If emotions were indeed bad, we would have been wiped out by ‘homo rationalis,’ but instead it’s we, emotional creatures, that wiped out the others.”
Neuroscience is necessary to pick up where other behavioral theories have left off, says Bossaerts, who studies value signals (how much utility the brain assigns to certain stimuli) to explain deviations from a particular theory. “At each point in that valuation process, things may go wrong or may be different from what the standard theory actually predicts,” he explains. “I’m trying to understand the algorithms that the brain uses to perceive uncertainty, to learn about uncertainty, to eventually lead to a choice under uncertainty.”
Bossaerts hopes this method of understanding the brain will ultimately lead to a revolution in the way economists and finance folks think about choices — not as the maximization of utility but as the outcome of a decision-making process. “The bottom line for finance, and in particular asset pricing, is that it is absolutely true — it works like that,” says Bossaerts. “Where it fails very often is that that theory is too tight; it doesn’t allow for any mistakes in these expectations.”
The insularity of academic disciplines has hindered progress, Bossaerts says. Economists are trained too much like historians, using past knowledge to mold their perceptions. Those in finance are mathematically bound, lean more toward natural philosophy and are not sufficiently experimentally minded. “Decision neuroscience allows us to get out of the straitjacket of revealed preference,” he says.
Yale’s Shiller agrees. In November 2011 he wrote an article titled “The Neuroeconomics Revolution” in which he explained how “revolutions in science tend to come from unexpected places” and how neuroscience is changing the way people think about economics. Shiller calls for collaboration among social scientists — psychologists, sociologists and economists — as well as among law professors, political scientists and mathematicians, to move the field of finance forward. “You have to have a synthesis,” he says. Shiller sees finance theory as “a sequence of little stories that are enlightening, but they end up trailing off and not going anywhere.” For example, “the CAPM is a brilliant story, but once you’ve heard it, there are a lot of contradictions, just as the theory of relativity contradicts quantum mechanics.”
麻省理工学院的LO是神经经济学革命的一部分。事实上，自20世纪90年代以来，他一直在接近交易商。“这都是相同的推力的一部分，我们正试图了解经济决策如何从生物学的角度来看，”他说。“我专注于生理学;[神经科学家]专注于脑成像。“最近，LO一直在努力纳入的CAPM版本，该版本包含进化生物学以及行为金融所确定的偏差。“这个理论意味着的事情之一是，风险奖励权衡我们所知道的，爱情随着时间的推移并不稳定，”他说。“自适应市场假设的一个含义之一是它随着时间的推移而不是固定的。它实际上改变了各种不同的情况。“
If all this sounds a little like Asimov’s psychohistory, that’s not a coincidence. There’s clearly an element of science fiction to the future of finance theory.
“The more we understand about the various elements of decision making, I think the more likely it is that we’ll develop a complete picture of how humans behave, and that’s really to me the Holy Grail,” says Lo. “But unlike the Holy Grail, I think that this is achievable within the next decade or two.” • •