Quotes and notes from Fischer Black and the Revolutionary Idea of Finance by Perry Mehrling
A cowardly fear of thinking curbs us all; the censorship of public opinion is more oppressive than that of governments. Most writers are no better than they are because they have ideas but no character … To be original you must listen to the voice of your heart rather than the clamor of the world --- and have the courage to teach publicly what you have learned. The source of all genius is sincerity; men would be wiser if they are more moral. (Ludwig Borne (1823), quoted in Rudolf Flesch, How to Make Sense (1954), quoted at the front page of the book)
Risk and time, he (Treynor) said, are the problems that define the modern field of finance, and Fischer Black’s proposed solutions to specific problems in the field should all be understood as bits of a larger proposed solution to those deeper problems. Fischer’s special genius was for developing models, “insightful, elegant models that changed the way we look at the world.” The most famous of these was the Black-Scholes formula that made possible the subsequent derivatives revolution on Wall Street, but there were others as well. (p. 6)
Fischer never took a course in either economics or finance, so he never learned the way you were supposed to do things. But that lack of training proved to be an advantage, Treynor suggested, since the traditional methods in those fields were better at producing academic careers than new knowledge. Fischer’s intellectual formation was instead in physics and mathematics, and his success in finance came from applying the methods of astrophysics. Lacking the ability to run controlled experiments on the stars, the astrophysist relies on careful observation and then imagination to find the simplicity underlying apparent complexity. In Fischer’s hands, the same habits of research turned out to be effective for producing new knowledge in finance. (p. 6)
Both CAPM and Black-Scholes are thus much simpler than the world they seek to illuminate, but according to Fischer that’s a good thing, not a bad thing. In a world where nothing is constant, complex models are inherently fragile, and are prone to break down when you lean on them too hard. Simple models are potentially more robust, and easier to adapt as the world changes. Fischer embraced simple models as his anchor in the flux because he thought they were more likely to survive Darwinian selection as the system changes. (p. 14)
John Cox, said it best, ‘Fischer is the only real genius I’ve ever met in finance. Other people, like Robert Merton or Stephen Ross, are just very smart and quick, but they think like me. Fischer came from someplace else entirely.” (p. 17)
The following passage is from the lecture notes by Clifford Geetz, a Harvard professor: “Production per se has thus become a central value in our society; our utopian image is the ever-expanding economy. Such an image, though it is held by some of the most prudent, realistic, and practical men in our society, is truly utopian for it rests on the false premise that the potentialities of the environment in which we live are infinite, that ‘science’ will always find a way to make any damage we do to nature unimportant and will enable us to go on forever milking the cow without feeding her.” (p. 34, Mehrling, 2005)
Fischer told himself that the job at ADL was more or less a continuation of his job at BBN, but with industry rather than the government as the primary client. One good thing was that such work was more likely to be of practical use to someone. At BBN, the culture was that consultants decide what they want to work on and then find some argument why the government should fund it. Fischer always thought this put the cart before the horse, and he looked forward to a different culture at ADL. (p. 47)
I had the same feeling when I
looked for a job at financial industry while I was working at a university. And
my experience at ING-Barings taught me a lot of things I could never learn from
reading books.
Practical experience is not merely the ultimate test of ideas; it is also the ultimate source. At their beginning, most ideas are dimly perceived. Ideas are most clearly viewed when presented as abstractions, hence the common assumption that academics --- who are proficient at presenting and discussing abstractions --- are the source of most ideas. (p. 6, Treynor, 1973) (quoted in p. 49)
Fischer Black learned the capital asset pricing model (CAPM) from Jack Treynor, but no one else did. Fischer and jack talked the same language, but everyone else talked economics. That’s why no one got the point when Treynor’s CAPM got passed around to the economists. CAPM would have to be invented again twice, and by economists this time, before the new idea could take root and grow. Only after the fact, indeed after the 1990 Nobel award shared by Harry Markowitz, William Sharpe, and Merton Miller, would economists be able to look back and recognize Treynor’s paper as an independent discovery of CAPM. (p. 73)
Lintner, by contrast, approached the problem from the perspective of a corporation issuing shares of stock. He got to his version of CAPM by extending the famous 1958 paper of Modigliani and Miller, the very same paper that got Treynor started. But Treynor wanted to build on Modigliani-Miller, while Lintner wanted to refute them. (P. 74)
Uncertainty, Lintner came to think, was the most important feature of the real world that was absent from the ideal world of Modigliani and Miller. His intuition told him that if you take into the account the effect of financial policy on the riskiness of the firm, then their results collapse. … In a nutshell, Lintner’s idea was that financial policy affects the firm by affecting the riskiness of future profit flows. (P. 79)
The whole point of his theoretical research had been to refute Modigliani-Miller by showing why shareholders care about variance, and hence why managers should care about the firm’s financial policy. But now the math was saying that shareholders care only about covariance which, in Lintner’s mind, had nothing to do with financial policy. He had intended to refute Modigliani-Miller, but wound up confirming them. And yet his intuition remained unshaken, based as it was on deep knowledge of how the world actually works. Schlaifer’s memo meant that he hadn’t yet identified exactly where Modigliani-Miller went wrong.
Uncertainty was still the most likely suspect, but apparently the uncertainty in CAPM was yet too idealized to capture the essential characteristics of the real world. Lintner’s 1969 CAPM paper would treat the more general case where individual investors have different information and different preferences, where short selling is limited, and where there is no rsikless asset to combine with the risky portfolio of stocks. And later still, the application of Black-Scholes option pricing to stock prices would provide a rigorous model in which total variance, not covariance, is what matters. … Total risk, he would argue, is the sum of business risk, financial risk, and market risk. (p. 84)
Lintner’s
intuition has been developed into an analytical theory (Chen, 2006).
I like the beauty and symmetry in Mr. Treynor’s equilibrium models so much that I started designing them myself. I worked on models in several areas:
Monetary theory
Business cycles
Options and warrants
For 20 years, I have been struggling to show people the beauty in these models to pass on knowledge I received from Mr. Treynor.
In monetary theory --- the theory of how money is related to economic activity --- I am still struggling. In business cycle theory --- the theory of fluctuation in the economy --- I am still struggling. In options and warrants, though, people see the beauty. (p. 93)
Fischer
Black may not realize that his breakthrough in options is much more
fundamental. It extended CAPM from one period to continuous time. With such a
continuous time framework slightly modified, ( Details from reverse
evolutionary equation (Black-Scholes equation) to evolutionary equation can be
found in Chen (2005)) the problem of business cycles can be understood very
easily. The key insight is that CAPM is a short term model and the continuous
time theory is a long term model. Business cycle, being a long term process,
can be more precisely described by a long term model.
The totality of our so-called knowledge or beliefs, from the most casual matters of geography and history to the profoundest laws of atomic physics or even pure mathematics and logic, is a man-made fabric which impinges on experience only along the edges. Or, to change the figure, total science is like a field of force whose boundary conditions are experience. A conflict with experience at the periphery occasions readjustment in the interior of the field. But the total filed is so underdetermined by it s boundary conditions, experience, that there is much latitude of choice as to what statements to reevaluate in the light of any single countray experience. W.V.O. Quine, “Two Dogmas of Empiricism” (1953, p. 42) (Quoted in p. 99)
Coming from economics, it was natural for Samuelson, and for Merton following him, to think of the option pricing problem from the point of view of the individual investor considering the range and probability of values that the option might have upon maturity, and then discounting those future values back to the present. From this point of view, it seems obvious that the current price of the optionmust depend on the investor’s attitude toward risk. Even more, since the option is more risky than the stock, it seems intuitive that, if the investor is to hold both the option and the stock, the expected return on the option must be higher than the expected return on the stock. How much higher must depend on both the investor’s attitude toward risk and the riskiness of the option, and just to make things harder) the riskiness of the option changes with the stock price. It seems like a complicated problem.
By contrast, coming from Treynor’s CAPM, it was natural for Black to think of the option pricing problem as essentially a matter of calculating exposure to market risk at a moment in time. And it was furthermore natural for him to proceed, following the method of Treynor, by writing down a differential equation describing how the value of the option changes over time. Black’s preferred CAPM approach to the problem appears in the published 1973 Black-Scholes article under the heading “An Alternative Derivation,” so it needs to be emphasized that this “alternative” was in fact the key that he used to unlock the problem in the first place. In 1969 Black was applying CAPM not only to options but also to lifetime investment strategy, to money and to business cycles. To understand how he was able to crack open the problem that had so far defeated everyone else, we must start where he started. (p. 128)
The
superiority of the approach in research in finance is that it is utility free.
Utility function is the reason why economic research falls behind.
McCloskey and Zecher saw their results as a consequence of international arbitrage in goods markets, a kind of extension of law of one price to nontradable goods, so they interpreted it as a confirmation of purchasing power parity. Fischer saw the same result as a consequence of international equilibrium that extends from financial markets down into commodity markets, so he interpreted it as a confirmation of what he called “the law of one equilibrium,” which says that market forces determine the relative prices of all goods independent of monetary factors. For Fischer, the purchasing power parity relationship was merely a corollary of this fundamental law.
In Fischer’s reading,
Market
force drives to equilibrium. But non-market forces are often there to maintain
non-equilibrium, such as wage differential by restriction on labor movement
across nations. The price mechanism is a reflection of both forces. Since labor
cost is a large portion of total price in many goods, price has to be
understood from the lens of restriction on labor movement. Indeed the whole world
structure of production and trade can be easily understood from restriction of
labor movements. For example, the dynamics of US-Mexico relation is largely
determined by the interaction of market force and non-market force. The market
force determines that people will flow from low wage
For Paul Samuelson, the acknowledged leader of the neo-Keynesian troika, the challenge of developing the basic science was fundamentally about bringing mathematical methods to bear on the development of economic theory. Just as in physics, “capture by mathematics” could confidently be expected to produce a flowering of basic theory, simply because mathematics was so much more convenient than natural language for drawing out a chain of deductive reasoning. By choosing mathematics as the language for economic theory, Samuelson argued, we can practically guarantee efficient and correct deduction of conclusions from premises.
Of course there is nothing in the convenience of mathematics to save us from big mistakes if we base our deduction on false premises. “Where the really big mistakes are made is in the formulation of premises.” Nevertheless for Samuelson and for the department he built around himself, the focus was on the deductions, not on the premises. …
Fischer was always more interested in the next new thing than in providing a systematic account of the state of knowledge so far achieved. And even his conception of what had been achieved was different. Finance, he thought, was not so much a collection of academic papers ringing the changes on a set of workhorse models. Rather it was more like a language, and learning finance was essentially about learning to construct grammatical sentences in the language of finance. His impulse, when faced with a new problem, was not to go to the blackboard and write down a mathematical model, but rather to talk around the problem, approaching it simultaneously from as many different angles as possible, and almost entirely with words, not mathematics. Formal modeling would come later, if at all, and only after the problem had been essentially solved.
The reason for emphasizing verbal treatments was to maintain maximal flexibility. Once you write down a model, you freeze the problem into a given intellectual framework and it becomes very difficult to consider alternative framework. … Indeed, Fischer’s intellectual strategy for developing new economic theory was almost exactly the opposite of Samuelson’s. Not mathematical problems but practical problems were the focus of his attention. And his approach to solving them was not to build up from simpler specific problems but rather to build down from a solution of more general problems. (p. 196)
Fischer adapted to the resulting sense of intellectual isolation by embracing a certain degree of physical isolation as well. He stayed in his office with the door shut, and did not respond to knocks. … Alone in his office he might have been anywhere. With isolation came intellectual freedom. (p. 198)
“Why do human capital and business have ups and downs that are largely unpredictable? I think it’s because of the basic uncertainty about what people will want in the future and about what the economy will be able to produce in the future.” … The idea that the problem was in the details of the sectoral match did not necessarily rule out a role for government, but it definitely ruled out the kind of aggregative and monetary policy interventions that were the focus of traditional macroeconomic debate. If Fischer was right, then intervention could be effective only to the extent it was able to help the private sector get the match right, in detail, which was a tall order to say the least. (p. 203)
Fischer had a different view. The volatility of stock price makes perfect sense if the world is nonstationary, as he believed it was. In a nonstationary world, the range of possible futures that investors need to assess in order to form estimates of current value is much wider than in a stationary world. … Firms must make investment and production decisions without knowing the details that they would have to know in order to be sure they were doing the right thing. If they are lucky, they will turn out to have guessed right, so they’ll be able to sell what they produce, and income values will be high. If they are unlucky, they will turn out to have guessed wrong, so they won’t be able to sell what they produce, and income values will be low. In the meantime, individual values will fluctuate because new information keeps coming in that causes us to change our estimates up or down. … Fischer’s theory thus offered no point of traction where traditional macroeconomists, of whatever stripe, could connect with Fischer or he with them. The result was that it was not Fischer Black, but rather Robert Lucas, who ushered in the revolution in macroeconomics that took place in the late 1970s. …With views like that, it is no wonder that Fischer had trouble publishing. There was simply no academic constituency for a theory that both Keynesians and monetarists saw, quite correctly, as providing aid and succor to their intellectual opponents. (p. 211)
I have a
similar problem myself. I criticize neoclassical economics on their theoretical
foundation and alternative theories for their lack of analytical framework.
Writing in 1972, Jack Treynor sounded an alarm. Corporations were promising pension benefits to their employees, but taking no very substantial steps to ensure their ability to fulfill on their promises. “Ultimately many pension beneficiaries are going to wake to find that their investment losses have deprived them of their main source of support in retirement.” Treynor urged that promised pension benefits be recognized as proper liabilities of the firm, and hence as claims not just to specifically designated pension fund assets but also to the general assets of the firm itself. In his mind, the ambiguous status of pension benefits served to disguise a fundamental conflict of interest. If the firm did well, shareholders enjoy the upside, while if the firm did poorly, pension beneficiaries absorbed the downside. The ambiguity served to increase current stock value to the benefit of shareholders, but only to the extent that pension promises were a fraud. ( p, 220, Mehrling, 2005)
It is marvelous that Jack Treynor
pointed out in 1972, long before pension problems surface seriously. It is also
marvelous that even today, after Jack Treynor pointed the problem more than 30
years ago, many established firms, such as auto manufacturers and airliners,
are still struggling with the problem of pension under funding. What has been
the main solution? How it affects the financial obligations of employers and
pension benefits to employees?
In 1972, Jack Treynor sounded another alarm in an article titled “The Trouble with Earnings.” This time his target was the accountant, “the oldest of the professionals in the investment industry,” and therefore the one most resistant to replacing craft with science, and the one most insistent on holding fast to “accounting ritual” in the face of rational judgment. The problem was that the most important output of the accounting ritual, namely a measure of “accounting earnings,” bears no very close relationship to the “economic earnings” that the security analyst wants for his calculation of the value of the firm.
In Treynor’s view, the security analyst poses a deadly threat to the accountant, since the security analyst’s modern and scientific method of judging the worth of a company is demonstrably superior. What the world wants to know is the value of the firm, not the change in value with which the accountant is obsessed. There is no room for both analyst and the accountant, because one is rational and the other is ritual. The best thing would be for the accountant to disclose as much information as he (or she ) knows about the firm, with as little ritualistic processing as possible, and leave the rest up to the analyst.
Fischer’s lifelong engagement with the problem of accounting starts here but characteristically he finds a more positive approach. Although there could be no question that the theories of modern finance require far-reaching changes in accounting practice, there could also be no question that at the end of the day the role of the accountant would remain important and distinct from that of the security analyst. Simple disclosure could not be the answer, because anything disclosed to the analyst is also disclosed to competitors. In this respect, “an accountant’s job is to conceal, not to reveal.” Even more, because the accountant is privy to a great deal of proprietary information inside the firm, he should in principle be able to produce a better estimate of the firm’s value than the analyst. The goal should therefore not to replace the accountant but to redirect his attention toward the task of estimating value. (p. 224, Mehrling, 2005)
Treynor’s path involved a career spent asking the question: How might an analyst add value in an efficient market? There are only two ways. Either he uses superior information or he applies superior reasoning to existing information. In his 1981 article “What does it take to Win the Trading Game?” Treynor writes: “Although the market is highly competitive, market efficiency as such should not prevent active investors from outperforming the market, by capitalizing on either inefficiencies in the propagation of information or inefficiencies in valuation.” “Information-based traders” exploit the first inefficiency by focusing their efforts on “investigation,” which means gathering superior information. “Value-based traders” exploit the second inefficiency by focusing their efforts on “analysis,” which means superior reasoning. For his own investment practice, Treynor saw greater opportunities in value-based trading. In his view, systematic errors in conventional asset valuation provides regular opportunities to earn excess returns.
In line with this view, Treynor’s favorite way to test an investment idea was to tell other people about it. If they understood the idea easily and agreed that it was a good idea, he would know that the idea was probably already reflected in the price and would move on to the next one. If they found the idea incoherent or unsound, then he would know that the idea was not in the price, and conclude that it was worth more careful study. (In the world of academia, Fischer adopted a recognizably similar approach to test his own intellectual ideas by laying outrageous views open for scrutiny in academic seminars. (p. 254)
There is one more parallel to draw.
If an idea gets accepted easily in the academic world, it is unlikely that it
is highly valuable.
Meanwhile, two of his oldest friends kept him company on his bedside table: Van Quine’s Quiddities: An Intermittently Philosophical Dictionary, and Noam Chomsky’s Knowledge of Language: It Nature, Origin and Use. He was thinking back to 1962-1963 when free from both Tinna and Harvard, he had begun to put in place the strategies of research and communication that had made possible his life’s work. (p. 285)
The way you change business practice, Fischer learned through experience, is by proposing something rather close to existing practice that people can actually implement. The way you change ideas, Fischer also discovered through experience, was very different. When he tried to frame his ideas in terms close to existing academic practice, he was ignored. He had more success in shifting the equilibrium when he stake out a position rather far away from it, and defended that position consistently and tenaciously.
Fischer’s strategy for changing the thinking in academic economics and finance was not only to stake out extreme positions, but also to solicit support for those positions from outside academia. His reason for publishing in the Financial Analysts Jouranl was not only that he found the standard economics journals largely closed to him, but also that the FAJ had a circulation 10 times that of even the best journals. The circulation did not include very many academics, to be sure, but it did include almost every important practitioner. By changing ideas on the ground, Fischer hoped eventually to change ideas in the ivory tower as well. Academia would follow where practice leads. (p. 295)
Says Fischer: “Government influence in teaching and research
is enormous. It leads, I believe, to a great loss of welfare.” … The obstacles
he had confronted in academia were, he came to conclude, a result of government
influence on the organization and functioning of the university,” … Fischer …
share his view on “Doctoral Education, the
The way to create a more free marketplace of ideas was, Fischer continued, to stop subsidizing the production of new ideas. Professors, he said, should be paid for their teaching only, since the ones who are not interested in research will stop producing it, and the ones who are interested in research will do it anyway. The result will be a net gain for society. Fewer noise traders relative to information traders in the marketplace of ideas can be expected to increase efficiency in that market. (p. 301)
Today, because the majority of
researchers are there to make a living, not for the interest of ideas. That is
why they are very hostile to new ideas, which will depreciate the value of
their own works. That is why a new scientific revolution is much more difficult
than an old one such as in Copernicus’ time, when there are few paid
researchers.
References
Chen, J. (2005) The
Physical Foundation of Economics: An Analytical Thermodynamic Theory, World
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Chen, J. (2006) Imperfect
Market or Imperfect Theory: A Unified Analytical Theory of Production and
Capital Structure of Firms, Corporate Finance Review, 11 (2006), No.
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