(转)Financial Modelers’ Manifesto

Preface

A spectre is haunting Markets – the spectre of illiquidity, frozen credit, and the failure of financial models.

Beginning with the 2007 collapse in subprime mortgages, financial markets have shifted to new regimes characterized by violent movements, epidemics of contagion from market to market, and almost unimaginable anomalies (who would have ever thought that swap spreads to Treasuries could go negative?). Familiar valuation models have become increasingly unreliable. Where is the risk manager that has not ascribed his losses to a once-in-a-century tsunami?

To this end, we have assembled in New York City and written the following manifesto.

Manifesto

In finance we study how to manage funds – from simple securities like dollars and yen, stocks and bonds to complex ones like futures and options, subprime CDOs and credit default swaps. We build financial models to estimate the fair value of securities, to estimate their risks and to show how those risks can be controlled. How can a model tell you the value of a security? And how did these models fail so badly in the case of the subprime CDO market?

Physics, because of its astonishing success at predicting the future behavior of material objects from their present state, has inspired most financial modeling. Physicists study the world by repeating the same experiments over and over again to discover forces and their almost magical mathematical laws. Galileo dropped balls off the leaning tower, giant teams in Geneva collide protons on protons, over and over again. If a law is proposed and its predictions contradict experiments, it’s back to the drawing board. The method works. The laws of atomic physics are accurate to more than ten decimal places.

It’s a different story with finance and economics, which are concerned with the mental world of monetary value. Financial theory has tried hard to emulate the style and elegance of physics in order to discover its own laws. But markets are made of people, who are influenced by events, by their ephemeral feelings about events and by their expectations of other people’s feelings. The truth is that there are no fundamental laws in finance. And even if there were, there is no way to run repeatable experiments to verify them.

You can hardly find a better example of confusedly elegant modeling than models of CDOs. The CDO research papers apply abstract probability theory to the price co-movements of thousands of mortgages. The relationships between so many mortgages can be vastly complex. The modelers, having built up their fantastical theory, need to make it useable; they resort to sweeping under the model’s rug all unknown dynamics; with the dirt ignored, all that’s left is a single number, called the default correlation. From the sublime to the elegantly ridiculous: all uncertainty is reduced to a single parameter that, when entered into the model by a trader, produces a CDO value. This over-reliance on probability and statistics is a severe limitation. Statistics is shallow description, quite unlike the deeper cause and effect of physics, and can’t easily capture the complex dynamics of default.

Models are at bottom tools for approximate thinking; they serve to transform your intuition about the future into a price for a security today. It’s easier to think intuitively about future housing prices, default rates and default correlations than it is about CDO prices. CDO models turn your guess about future housing prices, mortgage default rates and a simplistic default correlation into the model’s output: a current CDO price.

Our experience in the financial arena has taught us to be very humble in applying mathematics to markets, and to be extremely wary of ambitious theories, which are in the end trying to model human behavior. We like simplicity, but we like to remember that it is our models that are simple, not the world.

Unfortunately, the teachers of finance haven’t learned these lessons. You have only to glance at business school textbooks on finance to discover stilts of mathematical axioms supporting a house of numbered theorems, lemmas and results. Who would think that the textbook is at bottom dealing with people and money? It should be obvious to anyone with common sense that every financial axiom is wrong, and that finance can never in its wildest dreams be Euclid. Different endeavors, as Aristotle wrote, require different degrees of precision. Finance is not one of the natural sciences, and its invisible worm is its dark secret love of mathematical elegance and too much exactitude.

We do need models and mathematics – you cannot think about finance and economics without them – but one must never forget that models are not the world. Whenever we make a model of something involving human beings, we are trying to force the ugly stepsister’s foot into Cinderella’s pretty glass slipper. It doesn’t fit without cutting off some essential parts. And in cutting off parts for the sake of beauty and precision, models inevitably mask the true risk rather than exposing it. The most important question about any financial model is how wrong it is likely to be, and how useful it is despite its assumptions. You must start with models and then overlay them with common sense and experience.

Many academics imagine that one beautiful day we will find the ‘right’ model. But there is no right model, because the world changes in response to the ones we use. Progress in financial modeling is fleeting and temporary. Markets change and newer models become necessary. Simple clear models with explicit assumptions about small numbers of variables are therefore the best way to leverage your intuition without deluding yourself.

All models sweep dirt under the rug. A good model makes the absence of the dirt visible. In this regard, we believe that the Black-Scholes model of options valuation, now often unjustly maligned, is a model for models; it is clear and robust. Clear, because it is based on true engineering; it tells you how to manufacture an option out of stocks and bonds and what that will cost you, under ideal dirt-free circumstances that it defines. Its method of valuation is analogous to figuring out the price of a can of fruit salad from the cost of fruit, sugar, labor and transportation. The world of markets doesn’t exactly match the ideal circumstances Black-Scholes requires, but the model is robust because it allows an intelligent trader to qualitatively adjust for those mismatches. You know what you are assuming when you use the model, and you know exactly what has been swept out of view.

Building financial models is challenging and worthwhile: you need to combine the qualitative and the quantitative, imagination and observation, art and science, all in the service of finding approximate patterns in the behavior of markets and securities. The greatest danger is the age-old sin of idolatry. Financial markets are alive but a model, however beautiful, is an artifice. No matter how hard you try, you will not be able to breathe life into it. To confuse the model with the world is to embrace a future disaster driven by the belief that humans obey mathematical rules.

MODELERS OF ALL MARKETS, UNITE! You have nothing to lose but your illusions.

The Modelers’ Hippocratic Oath

~ I will remember that I didn’t make the world, and it doesn’t satisfy my equations.

~ Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.

~ I will never sacrifice reality for elegance without explaining why I have done so.

~ Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.

~ I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.

google translate
前言

一个幽灵正在市场 – 流动性不足的阴影,冻结信贷和金融模式的失败。

随着次级抵押贷款从2007年的崩溃,金融市场已转向以暴力运动,从市场的流行蔓延的特点,以市场的新政权,几乎不可想象的异常(谁又能有否想过,互换利差为负债可以去?)。熟悉的估值模型已经越来越不可靠。哪里是风险管理者没有归咎于他的损失,一个曾经在一个世纪海啸?

为此,我们聚集在纽约市和书面以下宣言。

宣言

在金融管理,我们研究如何从美元和日元一样,简单的证券股票和债券基金 – 像期货及期权,次级债务抵押债券和信用违约掉期复杂的。我们建立金融模型来估计证券的公平价值,估计其风险和如何进行风险是可以控制的。如何才能模型告诉你一个安全的价值呢?这些模式又是如何在不那么差劲的次级CDO市场呢?

比如物理,预测实物从目前国家的未来行为,因为其惊人的成功鼓舞了大多数金融建模。物理学家研究重复相同实验,一次又一次地发现几乎神奇的力量,他们的数学规律的世界。伽利略在比萨斜塔下降球,对质子碰撞质子在日内瓦巨人队,一遍又一遍。如果法律是相矛盾的建议和预测实验,回到了绘图板。这个方法有效。原子物理定律是精确到小数点后超过10个。

这是一个以金融和经济,这与货币价值的心理世界各不同的故事。金融理论竭力效仿的风格和优雅的物理学以发现其自身的规律。但市场是由人,谁是事件的影响,通过对事件的感性认识和他人的感受他们的期望。事实真相是,有没有在金融基本法律。而且即使有,也没有办法运行重复实验来验证。

你很难找到一个比稀里糊涂CDOs模型最更好的例子。 CDO的众多研究论文运用抽象概率理论的价格合作,抵押贷款数千架次。这么多的抵押贷款之间的关系复杂难辨。该营业员,建立了有自己的令人眼花缭乱的理论,需要使它可用,他们诉诸根据该模型的所有未知的互动,以地毯清扫,加上泥土被忽略,所有的左边是一个数字,称为违约相关性。从荒谬到崇高的优雅:所有的不确定性减少到一个单一的参数,当输入到模型由一名商人,产生CDO的价值。这种过度依赖概率和统计是一个严重的限制。统计是肤浅的描述,不像是更深层的原因和物理作用,并不能轻易得知违约的复杂动态。

模型是在底部的工具近似思想,他们成为改变你的直觉对未来的安全成为今天的价格。它更容易直观地认为对未来房价,违约率及违约相关性比是有关CDO价格。 CDO的模式把你对未来的房价猜测,按揭拖欠率和入模型的输出简单的违约相关性:1当前CDO的价格。

我们在金融领域的经验告诉我们要在应用数学的市场非常谦卑,是非常雄心勃勃的理论,这在人类行为的模型试图结束的警惕。我们喜欢简单,但我们要记住,这是我们的模型是简单的,而不是世界。

不幸的是,金融的教师都没有学习这些经验教训。你必须在金融业务上教科书只一眼发现数学公理高跷支持一个编号的定理,引理和成果的房子。谁会认为教科书在底部和金钱与人打交道?它应该是非常明显的常识,每一个金融公理是错的人,而且资金永远是在做梦欧几里德。不同的努力,正如亚里士多德说,需要不同程度的精度。金融是不是自然界科学之一,其无形的蠕虫病毒是黑暗的秘密热爱数学的优雅和太多的精确性。

我们需要模型和数学 – 你不能认为有关金融和经济没有他们 – 但千万不要忘记,一个模型是不是世界。每当我们做了一些涉及人类的模型,我们试图迫使灰姑娘的美丽水晶鞋公布于世的脚。它不适合没有切断一些必要的零件。而在切断,而不是揭露它的美丽和精确起见零件,模式不可避免地掩盖了真正的危险。关于任何金融模型最重要的问题是如何错了,它很可能是,尽管它的假设它是多么有用。你必须从模型,然后用常识和经验覆盖他们。

许多学者想像,一个美丽的一天,我们会找到’权利’模式。但是,没有正确的模式,因为在应对那些我们用世界的变化。在金融建模和进步是短暂的暂时的。市场的变化和新模式成为必要。约少量的变量简单清晰明确的假设模型,因此,最好的方式来充分利用你的直觉没有欺骗自己。

所有的地毯模式下扫污垢。一个好的模型使得污垢的情况下可见。在这方面,我们认为,选择估值Black – Scholes模型,现在经常无理指责的,是一个模型模型,它是明确的和强有力的。清除,因为它是真实的工程为基础,它告诉你如何制造出一种选择股票和债券,这将花费你什么,在理想的无尘情况下,它定义。其估价方法类似于搞清楚从水果,糖,劳工和运输成本的一个水果沙拉可以价格。世界市场的不完全匹配的Black – Scholes需要理想的情况,但该模型是一个强大的,因为它允许智能交易商调整的定性不匹配。你知道你是假设您使用该模型时,你确切地知道什么已经席卷了看法。

大厦财务模式是具有挑战性的和有价值的:你需要结合定性和定量,想象力和观察,艺术和科学,在寻找市场和证券服务的所有行为模式近似。最大的危险是偶像崇拜古老的罪恶。金融市场是活的,而是一个模型,但是美丽,是一种手段。不管你怎么努力,你将无法呼吸到它的生命。为了混淆视听,与世界模式是拥抱未来灾难的信念驱使人类服从数学规则。

对所有市场营业员,联合起来!你有什么可失去的只是你的幻想。

该建模人员’希波克拉底誓言

〜我会记得我并没有使世界,它不符合我的方程。

虽然我会大胆地使用模型来估计值〜,我不会有太多印象深刻的数学。

〜我永远不会牺牲典雅而不解释我为什么这样做的现实。

〜我也不会请人谁使用它的准确性我的模型虚假的安慰。相反,我会明确的假设和疏漏。

〜我知道,我的工作可能对社会和经济的巨大影响,其中许多是我无法理解。

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