Fund management is in crisis. For now the crisis is epistemological, but if its causes are not addressed, it threatens to become existential, for it is easy to forget how precocious the industry actually is. Insurance can trace its origins back to antiquity. Bond markets emerged to finance the governments of the early modern period. But equity investing is of much more recent provenance. Benjamin Graham did not publish Security Analysis before 1934, and The Intelligent Investor did not appear until 1949. Stock market listings by industrial and commercial companies were far from commonplace as recently as the 1950s, and most shares were owned by retail investors rather than large institutions advised by professional fund managers.
As recently as 1977, the total assets under management of the entire American mutual fund industry were worth just $50 billion. That same year Siegmund Warburg told Peter Stormonth Darling to “get rid” of Mercury Asset Management, the investment management subsidiary of S.G. Warburg & Co. that rode the 1980s bull market in equities successfully enough to become the largest and most successful independent fund management business in the United Kingdom. Yet Warburg tried repeatedly to close, sell or give it away, because he regarded investment management as unprofitable, a distraction from his primary business of giving disinterested advice to top-class companies and governments, and an activity almost as disreputable as stock broking. It was called Mercury because he refused to allow his name to be associated with it.
He scarcely could have been more wrong. By the late 1970s, investment management was on the cusp of a period of such explosive growth that Mercury Asset Management eventually fetched a price four times that of the whole of S.G. Warburg & Co. Far from being morally questionable, it was already seriously scientific. In fact, almost everything that has happened in investment management since the 1970s can be traced to the work of Harry Markowitz (the trade-off between risk and return, 1952), Franco Modigliani (the value of a company is unaffected by its capital structure, 1961), Merton Miller (ditto), William Sharpe (the distinction between diversifiable and non-diversifiable risk, or capital asset pricing model, 1964), Fischer Black (Black-Scholes options pricing model, 1973), Myron Scholes (ditto), Robert Merton (ditto) and Eugene Fama (efficient markets hypothesis, 1970).
My own 1986 copy of Principles of Corporate Finance by Richard Brealey and Stewart Myers, the standard textbook of MBA students in the 1980s, closes with a chapter titled “What we do and do not know about finance.” Among the things it thought we knew are NPVs calculated by discounting cash flows, the capital asset pricing model, efficient capital markets and the Black-Scholes formula. Had value at risk (calculation of maximum likely loss, © J.P. Morgan, 1994) been invented in 1986, it doubtless would have made the cut as the last word in risk management, and the description of all the theoretical tools of the financial crisis that erupted 21 years later would have been complete. Ironically, the text coyly concedes that “in ten or 20 years’ time we will probably have much better theories than we do now.” The problem is that we do not, despite the catastrophic failure of almost every aspect of modern financial theory over exactly that time span.
Today, only NPV retains respectability. Since the onset of the financial crisis, confidence in modern financial theory has collapsed. This failure is not a trivial one. The disastrous practical consequences of modern financial theory have undermined public confidence in the social utility as well as the moral standing of the entire capitalist system by creating repeated disasters that have cost taxpayers and savers trillions of dollars. Yet, ironically, it was because the risks of adopting the abstruse and abstract theories of economics and business school professors seemed so low that inadequate work-in-progress achieved such rapid penetration of an important industry.
Financial markets are a field in which the time lapse between the formulation of a theory in the academy and its application to reality is worryingly short, but the early adopters knew that the penalties for failure would be measured not in lives lost, but money lost— and that money would belong to other people too. Accordingly, profit-seekers have a strong incentive to adopt models that are useful at making money, even if they are half-baked. Besides, fund managers (especially large ones) are not really asset managers at all. They are asset gatherers, and asset gatherers are salesmen, and salesmen are storytellers. They use narratives so instinctively that they even have genres (value investing, quantitative value, capital cycle and so on). It is easy for them to slip from making well-founded predictions into ill-founded prophecies, especially if it helps them gather assets. Financial theory is a powerful tool for persuading investors that investment is a scientific discipline whose risks are manageable. In short, modern financial theory may not be true, but it is useful.
The Modigliani-Miller theorem, for example, was useful because it provided a clear intellectual justification for excessive leverage (which multiplied returns on equity) and for cutting dividends (which helped preserve the value of the stock options held by senior managers). Yet the correspondence of the theorem with reality was always limited. It assumed companies and individuals could borrow at the same rate, wished away the differential tax treatment of equity and debt, ignored the transaction costs of raising debt or equity and failed to perceive the intrinsic conflict of interest between managers and shareholders.
Likewise, the modern portfolio theory invented by Harry Markowitz was useful to commercial interests because it appeared to give investment managers an irreproachably sound technique to assemble optimal portfolios of investments to deliver any combination of risk and return, plus a tool to manage the impact of new investments on the risk (beta) and return (alpha) of those portfolios. It took the computing power of the 1980s to really make use of this invention, empowering it to spawn not only a variety of pseudo-scientific asset allocation models but a seam of securitized and structured innovations designed to provide just the right combinations of alpha and beta.
Yet the most influential contribution of modern portfolio theory to the intellectual disaster that is modern investment management was its own inability to manage the correlations between the different assets in any given portfolio, given the shortage of historical price data and the lack of the requisite computing power to process what data there was. The solution came in the form of the capital asset pricing model (CAPM), which wished the problem away simply by assuming that every investor held a portfolio that mirrored the aggregate market risk and a risk-free asset. This model appeared to enable investors to measure the risk they cared about most because they could not avoid it (namely, the aggregate market risk, or what we now call beta) while also enabling them to measure the riskiness of any individual asset in that portfolio (each asset now had its own beta). Of course, what the CAPM really did was make a series of heroically unrealistic assumptions: that an aggregate market portfolio can be identified, that betas can be calculated reliably and that those betas remain stable over time.
As it happens, the reliability of the betas calculated under the CAPM was eventually demolished in 1993 by the man whose own theory was the most influential in creating the problems that ended in the financial crisis. This was Fama, who also formulated the efficient markets hypothesis.
This holds that competition among profit-seeking participants ensures that prices in financial markets reflect a consensus among investors about the net present value of future cash flows because prices adjust continuously to reflect all publicly available information. Any price discrepancies between market value and fair value are swiftly corrected by arbitrageurs collecting the resultant profits. The apparently random motion of stock prices, and the consistent inability of investment managers to outperform the market, is even now taken as proof that markets are efficient. In its early years, it fueled the growth of a massively profitable product for the investment management industry: indexation. Wells Fargo developed the first in 1973, and Jack Bogle sold his first indexed fund for retail investors in 1975. Less obviously, in tandem with the CAPM, the efficient markets hypothesis powered the notion that asset allocation is more important than stock selection. This remains a staple of fund management sales pitches.
Yet the efficient markets hypothesis struggled from the outset to explain “fat tails”— those outliers to the “normal” bell curve distribution of prices—such as the overvaluation of TMT stocks in 1999-2000 or the stock market crash of Oct. 23, 1987. Another problem, that some investors do manage to beat the market, was explained away as a case of outliers. The lucky few had either understood the market better on a temporary basis, or took on more risk, or just got lucky in their investments, or even their timing of their entrances and exits. Paradoxically, the consensus about the accuracy of the efficient markets hypothesis did not undermine the value of the investment advice offered by investment managers.
The idea that it was possible to beat the market through excellent advice was somehow able to coexist with the idea that it is impossible to beat the market even with excellent advice. However, the most substantial contribution made by the efficient market hypothesis to the financial crisis was its confident assertion that markets are always correctly priced. This effectively emasculated monetary policy in the face of overwhelming evidence of asset price inflation in the equity markets from 1987 to 2007. For fund managers, it provided the reassurance of the “Greenspan put.”
One reason Alan Greenspan was so ready to flood the market with liquidity at every stopping point in the long bull market that began in the early 1980s was his confidence in the risk-reducing and risk-sharing benefits of the finest product of modern financial theory: derivatives. As he made clear in a speech in Chicago in 2003, Greenspan thought derivatives enabled counterparties to “craft contracts that transfer risks in the most effective way to those most willing and financially capable of absorbing them.”
Chicago was of course the birthplace of modern financial derivatives, which were embraced enthusiastically after Black, Scholes and Merton solved the problem of how to value a call option in the early 1970s. That their solution made a familiar series of unrealistic assumptions about market realities—trading without transaction costs, perfectly liquid markets, no restrictions on short selling and especially constant price volatilities—could not outweigh the manifest usefulness of a pricing technique to the options traders of Chicago.
It soon spread far beyond the Windy City. The Black-Scholes-Merton pricing model was the foundation not only of the open outcry futures and options markets that developed throughout the world in the late 1970s and early 1980s but of the OTC derivatives that followed in the interest rate, equity, foreign exchange, credit and foreign exchange markets. Their usefulness to fund managers was obvious. Risk could be quantified, adopted and hedged. Tax and regulatory obstructions could be skirted. Capital requirements could be avoided. Above all, clients could be bamboozled into purchasing high-margin derivative products.
So it was no accident that quantitative fund managers were first into the financial crisis in 2007. Many quantitative managers had actually studied under the authors of modern financial theory, and all of them were influenced by its findings. Mathematicians, engineers and physicists found they could make far more money on Wall Street than at Los Alamos. In addition, financial markets generate oceans of data, and store it for decades, furnishing them with an embarrassment of information on which to test and back-test the algorithms invented by their intellectual gurus. This data could be fed into models based on the single biggest intellectual and methodological flaw in modern financial theory: that prices are distributed normally, and extreme events are extremely unlikely.
Nassim Nicholas Taleb has made a second career of pointing out that these “black swans” occur more often than they are expected, but his basic argument was made by Benoit Mandelbrot as long ago as the early 1960s, and the Options Clearing Corporation has used different distribution models since the 1980s. In the summer of 2007, the then-CFO of Goldman Sachs famously declared himself puzzled to be “seeing things that were 25-standard-deviation events, several days in a row.” Since his models told him that it would take more years for this to happen than there are particles in the known universe, it is surprising that investment banks, let alone investment managers, have not since jettisoned everything they thought they knew about how financial markets worked.
They have not, partly because they have not paid the ultimate price for such a catastrophic failure of judgment, but mainly because no fresh techniques have emerged. The term value at risk—which demonstrably led to excessive risk taking at banks by creating direct incentives as well as a false sense of security—still warranted 55 separate mentions in the Goldman Sachs annual report for 2011. Yet the VaR model, like the whole pseudo-science of risk management, is ultimately based on a string of unrealistic assumptions. They include the supposition that prices in financial markets move randomly but continuously, that events are independent of each other, that volatilities are measurable and stable, that correlations do not fluctuate, that data sets are undistorted and sufficient in size and history, that markets are liquid and that the actions of market participants themselves have no effect on outcomes.
The underestimation of the human factor is intrinsic to such quantitative information processing. As Greg Smith wrote of his quantitative fund management clients as they imploded in 2007, their models did not “effectively take the outside world into account. They do not have human thoughts, so psychology can never figure into their calculations. … They cannot look into the whites of people’s eyes and see their fear.” The whole of modern financial theory is as desiccated. It treats prices in markets as an abstract output, when in fact even the theory can be read as explaining that prices are determined by the interaction of traders, fund managers and investors competing to get the better of each other. Distressed sellers are attacked by predators. Traders deliberately mark prices down.
Market-makers stop answering the telephone. Modern financial theory does a poor job of describing reality, let alone explaining it.
It is the very human inefficiency of markets, not their efficiency, which allows extraordinary profits to accrue to some fund managers. Those managers tend to be in possession of superior technology or knowledge or information—occasionally illicit, as recent events have shown—but it is always temporary. Their advantage is soon competed away by better ideas or cleverer strategies or more powerful technology or even a regulatory clampdown. In this (weak) sense, the efficient markets hypothesis is “true” after all. Prices can be disturbed only by new information, which they then incorporate, and it is obvious that market participants do indeed react quickly to new information, selling stocks when a company announces bad results and buying stocks when a takeover looms.
But prices are really determined by people acting on the information, not by the information itself. This presents investment managers with a serious epistemological problem common to any endeavor with scientific pretensions. Investors and fund managers and traders are making decisions today to achieve results that will not be known until tomorrow. Nobody knows what will happen tomorrow, because the outcome will be affected by new information that will be created by the decisions of the previous day—and by new information that has yet to be discovered or new knowledge that has yet to be invented.
Since it is physically impossible to predict the content of future information or knowledge, errors in decision-making today are inescapable. It follows that investment management ought really to be about managing that disagreeable reality. Warren Buffet famously manages the risk of error by looking for impregnable business franchises. But orthodox fund managers still attempt, in their different ways, to predict the future. Value investors, for example, filter financial information about listed companies, such as their earnings and competitive position, and look to buy and hold stocks that they think will rise in price because their stock market valuation is below their fair value.
Managers that “trade” operate on a shorter timescale. They trawl through prices, looking for patterns and inefficiencies to exploit, simply selling what they think will fall in price and buying what they expect will rise in price, hour by passing hour and day by passing day. But fund managers are of course not the only participants in the markets. Market makers are active too, buying and selling continuously in response to orders, and getting paid for supplying liquidity. Then there are pure sellers. They just need cash, and have to sell what they have to obtain it.
It follows that financial markets cannot be what the efficient markets hypothesis holds them to be: efficient price discovery mechanisms populated by rational investors and arbitrageurs. Investors are mostly risk averse, proceed largely by trial and error and are never able to put their decisions into effect instantaneously anyway. Most process information ineptly or inadequately (most fund managers preferred agency ratings to scrutinizing the quality of the paper underlying CDOs, for example). Markets are complex adaptive systems in which information is dispersed and prices are riven by the interacting and competing investment strategies of market participants with different values, attitudes and goals.
Every participant interacts with every other participant. Their actions influence each other. A value investor that places a large order can expect the market maker to put the price of the stock up or down in reaction to it. The trader, seeing the price move accordingly, will buy or sell to profit from the upward or downward momentum. All investors make investment decisions based less on information than on their best guesses about what other market participants will do. In other words, fund managers and investors do not simply re-evaluate securities rationally as fresh information emerges, but interact with, compete with and react to each other, learning from each other and adapting their strategies accordingly. In effect, fund managers and investors are engaged in a constant competitive search for profitable strategies and look to replicate what works. They reinvest their earnings, or add leverage to reinforce their successful decisions with bigger bets, giving security prices a momentum that can drive them far from their fundamental values.
This is why stock markets have acquired a reputation for being driven by fear and greed. Prolonged errors of optimism (bull markets) and pessimism (bear markets) owe nothing to rational valuations of the prices of securities. They owe everything to the expectations of market participants about the behavior of other market participants. What one investor does depends on what other investors expect him to do, which in turn depends on what that investor expects other investors to do, and so on. It means that financial markets in periods of excess in either direction are in the grip of an infinite regress in which the argument for buying or selling depends on the influence of the argument for buying or selling.
This is why John Maynard Keynes famously likened the stock market to a newspaper beauty contest in which the winners are the readers whose choice corresponds most closely to the average preferences of all the readers that take part. Winning, as Keynes pointed out, depends not on selecting the most beautiful contestants, but the most popular. “It is not a case of choosing those that, to the best of one’s judgment, are really the prettiest, nor even those that average opinion genuinely thinks the prettiest,” he wrote. “We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practice the fourth, fifth and higher degrees.”
Of course, other factors—notably leverage, but also portfolio insurance and strict avoidance of tracking error—also play a part in stoking booms and deflating bubbles, but the fundamental problem is a repetitive cycle driven to erroneous excess by competing expectations amid chronic strategic uncertainty. This is the best current explanation of how financial markets work, and its inner workings are beyond the grasp of modern financial theory. Even the investment opportunities this explanation presents are virtually impossible to seize. In theory, the consequent misalignments create opportunities to make abnormal profits, most obviously by selling booms or buying busts at the right times. But that entails having the ability to identify abnormally profitable opportunities and then having the means to exploit them on a sufficient scale.
Though the Sharpe ratio pretends to identify opportunities by measuring returns relative to risk, the reality is that “fat tails” mean it can take years to work out if excess returns are sustainable rather than just lucky. Worse, accessing enough investment capital in time to exploit abnormally profitable opportunities efficiently makes assumptions about capital raising that are utterly unrealistic. It also takes years for a fund manager to establish a track record, and even more years to raise capital on the back of it, by which time the opportunities have usually evaporated. That may be disappointing, but it is reality.
At present, there is no solution to these problems, despite the popularity in some circles of game theory as a guide to human behavior. But that does not mean no solutions exist. To find them, a good start would be to gather and analyze what data is available to create the fresh knowledge that might break the pattern of failure. Another idea is to experiment with structural changes, such as investment vehicles that are neither securities nor derivatives. Certainly, alternative solutions are badly needed, because financial markets are locked into alternating patterns of bias, first to optimism and then to pessimism, and have a marked tendency to overshoot in both directions.
The inability of financial market theory to explain and control market phenomena of this kind raises profound questions about the usefulness of fund management as an institutional discipline. Reliance on past data to make investment decisions and manage risks has severe limitations. This is not only because past prices were driven by factors other than rational valuation and show wide dispersion around fair value. Market participants are also actively mining the historical price data, rendering it equally useless as a guide to the validity of prices now. In reality, investment strategies can prove themselves only by experience, and even then success might owe more to luck than judgment.
Nor is that all. The professional intermediaries interacting with each other in the financial markets have goals that are imperfectly aligned with those of their clients. In modern financial markets, end investors have sub-contracted asset management to fund managers, which have goals of their own and which in turn interact in the markets not only with other fund managers but with proprietary, technical and high-frequency traders. To see all of these intermediaries as rational, profit-seeking participants that have simultaneous access to the same information, and whose activities ensure that prices adjust continuously to reflect that information, is unrealistic to the point of caricature.
It is obvious that market insiders possess superior skills and technology, and especially better information. Their inability to beat the market benchmarks almost certainly owes less to the efficiency of the markets than their ability to exploit information asymmetries in relation to their clients. In other words, they are preempting most if not all of the alpha for themselves. The more successful managers lure capital away from their less successful competitors and press it into the service of the bets they have laid, making them both more right and more wrong. Prices may eventually revert to fair value, but momentum in either direction can push the price of securities an awfully long way from fair value for prolonged periods.
If momentum is the primary determinant of stock prices, and it drives stock prices far from fair value, this has implications far beyond the financial markets themselves. It means the cost of capital raised by companies is grossly distorted and that stock prices are an inadequate measure of the value of a company. Yet “shareholder value” is still the principal determinant of the success of a company, to such an extent that managements are rewarded by their ability to deliver it. Yet management has depressingly little influence over the value of a company.
A study by McKinsey found that two-thirds of the returns of individual companies could be explained by broader market factors and only one-third by factors specific to the company, let alone the management. The unacknowledged truth is that the real beneficiaries of modern stock market capitalism are not investors but their agents in the great fund management houses and in the boardrooms of the companies in which they invest. Fund managers are agents of investors. They trade claims on real assets and income streams of publicly and privately owned companies that are in turn managed by other agents, who are more likely to manage companies to enrich themselves than enrich their shareholders. This separation of the rights of ownership from the responsibilities of ownership—what economists call the “principal-agent problem”—is a massive structural fault in modern finance-capitalism. Fund management, as it is organized and directed today, is a symptom of it.
The oddity is that nothing meaningful is being done to address either the intellectual or the structural flaws that plague the fund management industry, save the usual placebo of regulation and the perverse consequences that invariably flow from it. Yet it is not as if these issues have stolen upon us in the last five years.
Berle and Means first explained the malign consequences of the separation of ownership from control in 1932. This year marks the 50th anniversary of the publication of the paper in which Mandelbrot explained that stock prices are not normally distributed. This summer, a decade and half will have passed since Long Term Capital Management failed, proving that all of the tools and techniques of modern financial theory have strictly limited explanatory and predictive power. It is a measure of the influence of entrenched interest, as well as intellectual bankruptcy, that they remain in use today. Despite accumulating evidence to the contrary, the fund management industry is proceeding on the basis that it possesses sufficient knowledge to measure and price risk. Its failures prove that it does not.
All failure is rooted in the lack of sufficient knowledge. What distinguishes progressive disciplines from unprogressive ones is the willingness to act on that insight. The only rational approach to the management of an inherently unknowable future is for hard minds to embark on the difficult task of speculating about what better techniques can be devised for the measurement and management of risk and return in financial markets. There is no sphere of human endeavor where knowledge cannot increase if minds are open to it. Those increases in knowledge will be incremental at first, but, if investment management follows the example of other disciplines, gradual improvements will one day lead to a sudden but massive increase in explanatory power and social utility.
The entire present paraphernalia of financial theory will be overthrown and replaced by a new set of ideas. A science-based, unified theory of finance that is capable of universal application is not a pipedream. Nothing in the laws of nature forbids it. Arriving at such an understanding will not be easy, for the problems the investment management industry confronts today are by their nature intractable.
But the industry could at least open its mind to the possibility that the current state of its knowledge is delinquent.