爱思英语编者按：诺贝尔经济学奖（The Prize in Economic Sciences），是由瑞典银行在1968年，为纪念诺贝尔而增设的并非诺贝尔遗嘱中提到的五大奖励领域之一，全称为“纪念阿尔弗雷德·诺贝尔瑞典银行经济学奖（The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel）”，通常称为诺贝尔经济学奖（Nobel economics prize），也称瑞典银行经济学奖。经济学奖并非根据阿尔弗雷德·诺贝尔的遗嘱所设立的，但在评选步骤、授奖仪式方面，与诺贝尔奖相似。奖项由瑞典皇家科学院每年颁发一次，遵循对人类利益做出最大贡献的原则给奖。1969年（瑞典银行的300周年庆典）第一次颁奖，由挪威人弗里希和荷兰人扬·廷贝亨共同获得，美国经济学家萨缪尔森、弗里德曼等人均获得过此奖。
The Nobel prize for economics
The right option
ECONOMISTS may sometimes seem about as useful as a chocolate tea-pot, but as this year's Nobel prize for economics shows, it isn't always so. On October 14th, the $1m prize was awarded to two Americans, Robert Merton, of Harvard University, and Myron Scholes, of Stanford University. Their prize-winning work involves precisely the sort of mind-boggling mathematical formulae that usually cause non-economists either to snooze or scream. That is too bad, for it ranks among the most useful work that economics has produced.
经济学家有时可能看起来中看不中用，但是，正如今年的诺贝尔经济学奖所示，这并非向来如此。10月14日，100万美元奖金被授予了两位美国人——哈佛大学的罗伯特·默顿（Robert Merton）和斯坦福大学的迈伦·斯科尔斯（Myron Scholes）。他们的获奖研究所涉及的正是那类通常让非经济学家昏昏欲睡或惊声尖叫的让人头大的数学公式。鉴于这个公式位列经济学所生产的最实用的研究，这太糟糕了。
What Mr Merton and Mr Scholes did, back in 1973, was to put a price on risk. Their work on how to price financial options, carried out with the late Fischer Black, turned risk management from a guessing game into a science. The complex Black-Scholes option pricing model (“It should probably be called the Black-Merton-Scholes paper,” Mr Black once said) and its subsequent evolutions, led to explosive growth in stock options and other financial derivatives. It also opened the era of the Wall Street rocket-scientist, a strategist schooled in physics or mathematics who makes money crunching numbers rather than playing hunches.
回到1973年，默顿和斯科尔斯当时的所为就是为风险定价。他们与已故的费希尔·布莱克（Fischer Black）共同进行的有关如何为金融期权定价的研究，将风险管理从一种猜谜游戏变成了一门科学。复杂的布莱克一斯科尔斯期权定价模型（Black-Scholes option pricing model）（布莱克曾经表示：“它或许应当被叫做布莱克-默顿-斯科尔斯论文。”）以及随后的演进，导致了股票期权和其他金融衍生品的爆炸式增长。它还开启了华尔街分析师是专业为数学或物理学的高智力人才时代。
Although derivatives often come dressed up in fancy names, among them swaptions and quantos, they really boil down to two basic sorts of financial instrument: forward contracts and options. A forward commits the user to buying or selling an asset—say a Treasury bill, or dollars—at a specific price on a specific date in the future. It is rather easy to price. The main difficulty is working out the cost of carrying the asset until it changes hands.
尽管衍生品经常是披着五花八门的名字出现，如互换期权 （swaptions） 和汇率连动期权（quantos）等等。但是，它们归根结底是两类基本的金融工具：远期合约和期权。远期合约保证使用者可以在将来的某个特定日期以特定价格买卖某种资产，如财政部债券或美元。给它定价非常容易，主要困难是计算持有这种资产直至换手的成本。
An option gives the buyer the right, but not the obligation, to sell or buy a particular asset at a particular price, on or before a specified date. Pricing one is a trickier affair, as it involves putting a number on the probability that a buyer will exercise his option. Until 1973 that was largely a matter of guesswork—which is why, though options first arose centuries earlier, the market for them remained tiny. But the Black-Scholes formula was published in May 1973, just after the world's first options exchange had opened in Chicago. Within a year it was being used by every trader. The rest, as they say, is history.
The economists found what mathematicians call a “closed-form solution”. In essence this meant that sellers of options could bung in a number of variables and the model would churn out a price. The big advantage of the formula is that it does not require option sellers to take a view on which way the price of the underlying asset will move. It is not entirely fool-proof: some of the variables, such as the risk-free interest-rate and the volatility of the underlying asset, may change over time. Also, the formula does not deal well with very large price movements. Nonetheless, the Black-Scholes formula gave option sellers a far more precise way to work out what an option is worth.
The option-pricing work of Messrs Black, Merton and Scholes was based on a clever and fundamental insight. This was that any asset, from a government bond to a bar of gold, is essentially a mixture of forward contracts and options. By, in effect, breaking down assets into constituent parts, it is possible to get rid of precisely those risks you do not want to keep and take on precisely those that you do. Breaking assets into their core bits allows the canny investor to spot cases where—hidden in, say, an Italian bond, or an American mortgage-backed security—certain sorts of risk are over-or underpriced relative to the market average. Arbitraging these price differences away has earned Wall Street a good deal of money.
This sort of arbitrage is precisely what Mr Merton and Mr Scholes are doing through Long-Term Capital Management, a hedge fund they helped create three years ago. Typically, the fund has around 20 highly diversified active investments in place around the world at any one time, with all but the precise risks the firm wants to bear hedged. The results have been impressive: high returns, with low volatility—every investor's dream. Already, the fund is said to have earned its founders profits of $1 billion. Thanks to the widespread use of their formula, however, such arbitrage opportunities are becoming rarer. Indeed, Long-Term Capital Management is returning to clients a large chunk of the $6 billion it manages because it cannot find enough opportunities in which to invest. Perhaps its begetters should have kept their bright idea to themselves.
Setting a price on the future
The mathematics of markets
The formula that changed finance
Pricing the Future: Finance, Physics, and the 300-Year Journey to the Black-Scholes Equation. By George Szpiro. Basic Books; 298 pages; $28 and £18.99.
OPTIONS and futures are almost as old as trade itself. From the farmer who sold his crop before the harvest to the merchant who bought at a set price in the future, the forerunners of today's markets can be traced to ancient Greece and Rome. Yet for centuries these markets remained stunted because of a simple question of valuation. What is the right to buy next year's olive crop worth? Answering this question took centuries of study of physics, botany and mathematics. When solved, it changed finance for ever.
The tale includes a fascinating succession of people who tried doggedly to master probability and markets. It is engagingly told by George Szpiro, a mathematician- turned-journalist, who flits between biographies and formulae. He begins with the futures and options markets of the tulip bubble of the 1630s. He looks at Napoleon's attempt to regulate trading with a modern-sounding ban on futures contracts and short sales. And he explores those whom history has forgotten, such as Jules Regnault, a self-taught broker's assistant who started working on the Paris Bourse in 1862. After seeing how share prices changed over time, he wrote a book on the subject and made a fortune trading shares. Regnault's writings have been largely forgotten, but his work foreshadowed modern financial theory.
故事包括一众相继不屈不挠地试图去掌握可能性并主宰市场的令人心动之人。它被游走与传记和公式之间的乔治·斯皮罗（George Szpiro），这位由数学家转行而来的记者，娓娓地讲了出来。他从17世纪30年代的郁金香泡沫时期的期货和期权市场讲起，说到了拿破仑试图用一种具有现代意味的期货合约和卖空禁令去监管交易的尝试，梳理了那些历史已被遗忘的人物，如1862年开始在巴黎证券交易所开始工作的自学成才的股票经纪人助手朱利·荷纽(Jules Regnault)。在看到股价如何随时间变动后，他就这个主题写了一本书并依靠买卖股票发了财。荷纽的文章大部分已被忘记，但是，它的研究昭示了现代金融理论。
Another great mind whose work was lost was Wolfgang Döblin. The son of a prominent German novelist of Jewish descent, Döblin fled Berlin to Paris in the 1930s. He obtained his PhD in mathematics at the Sorbonne, where he soon established himself as a pioneering mathematician and innovator in the field of probability. With war approaching, Döblin joined the French army in a gesture of gratitude to the country that had sheltered him. In his billet on the front-lines, he scribbled on a cheap school notebook, sketching out a formula that he sealed in an envelope and posted to the Académie des Sciences in Paris. Soon after, with his regiment surrounded and the French army in retreat, he burned his personal papers and, fearing what would happen if was captured by German soldiers, shot himself.
The envelope lay sealed in archives until May 2000, when it was found to contain the mathematical tools to describe the random movements of particles. Calculations such as these transformed people's understanding of physics and provided an important building block of the so-called Black-Scholes equation.
That equation, which Robert Merton, Myron Scholes and Fischer Black worked out in 1973, turned out to be a breakthrough that promised accurate assessments of the value of options, which are the right (but not the obligation) to buy or sell something at a particular price on some future date. Mr Merton and Mr Scholes were awarded the Nobel prize for their work on this in 1997. Black, who died in 1995, was also credited for his contribution.
The equation's publication led to a flowering of options markets and an explosion of trading on them. It also transformed investment banking and stockbroking. The affable trader who calculated prices and odds by the seat of his pants on the trading floor, much as a gambler did at the poker table, was supplanted by the “quant”, a mathematician with a room full of computers and reams of data.
Yet the model has deep failings. Black-Scholes assumes that movements in share prices, like those of particles suspended in liquid, can be plotted using a Gaussian, or bell curve, distribution. Yet finance is filled with “fat tailed” events that occur far more frequently than predicted by this model of the physical world. Black-Scholes reached its zenith in 1998, just before the collapse of Long-Term Capital Management (LTCM), an investment firm backed by the two Nobel prize-winning economists.
LTCM failed when the yields on bonds issued by countries such as Russia and America began to diverge, something the models said was virtually impossible. A decade later the great financial crisis was ushered in by the simultaneous collapse of house prices across America, another event that the mathematical models said was virtually impossible. In both instances, financial firms quickly found themselves racking up daily losses that the computers said should occur only once in millions of years.
“Pricing the Future” is at its best when it skips through the parallel developments in physics, mathematics and economics that led to the equation, a development that Mr Szpiro compares to the discovery of the structure of DNA or Isaac Newton's laws of motion. Unfortunately, Mr Szpiro's narrative dodges some important questions that it ought to have delved into in detail. In just four pages the book describes, almost as an afterthought, the failings of the Black-Scholes model and the history of the past decade since the collapse of LTCM. Black-Scholes may well have been a great achievement, but histories of the financial crisis will treat it less than kindly. The quest to tame risk and price the future is far from over.