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CHAPTER 1
Meeting the Predictors
In spring 2010, it seemed as if the financial crisis had come to an end. Governments had bailed out many of the so-called systemically relevant banks, and stock markets appeared to be slowly recovering. The tragic effects of the financial crisis were visible, however, in struggling industries and growing unemployment. Countries such as Greece and Spain reported youth unemployment rates of more than 50 percent, while at the same time governments lowered their spending to unprecedented levels. Furthermore, as a direct consequence of housing market speculation, approximately 10 million homeowners had lost their homes in the United States alone. Most financial market participants claimed, nevertheless, that the financial markets seemed to have overcome the crisis.
This optimistic view did not last long. On May 7, 2010, I was supposed to meet with a member of the financial analysis department I was aiming to study. At 9:12 a.m., my cell phone rang: "I don't know whether you've already seen it," the caller said, "but the markets are going crazy. I'm afraid we have to cancel our meeting." I had no idea what the person was referring to, and so I went online to find out. It turned out that, at 2:45 p.m. New York time on May 6, the Dow Jones Industrial Average Index, one of the most important stock market benchmark indices, lost 9 percent of its value within a few minutes. Although the exact reasons for the Flash Crash, as this incident came to be known, have been subject to discussion ever since, one thing became clear to me that day: however legitimate they might look, financial market forecasts can become useless very quickly. In fact, predicting market developments is — as some financial analysts themselves like to say — often simply "betting on the future." The same insight ultimately applied to the long-term development of the overall financial crisis after this particular moment in 2010. Instead of experiencing the aftermath of the crisis, I became witness to the "currency wars" ("Currency Wars," 2010), an economy "on the edge" ("On the Edge," 2011), and what was almost the end of the euro ("Is This Really the End?" 2011). In other words, I observed the sad continuation of the biggest financial crisis since the Great Depression.
I joined Swiss Bank (a pseudonym I use throughout this book) in September 2010 for a two-year fieldwork phase because I wanted to understand what happens inside one of today's biggest black boxes: the banking world. I was born and raised in Zurich, the home of the two major Swiss banks, as well as dozens of small and medium-sized financial institutions. Even though Zurich is massively influenced by its financial sector, which contributes no less than 22 percent of the canton's GDP (Kanton Zürich 2011, 7), the sector has remained opaque to many of the people of Zurich. This opacity results partly from the fact that its employees rarely discuss their work in public. Also, Swiss banks have done a good job of presenting the banking sector as a simple service industry, rather than as a field of powerful corporate actors who heavily influence their host cities and dominate much of the world's economy.
The figures speak for themselves: In 2005, the total assets held in Swiss bank accounts were worth eight times Switzerland's GDP (in the United States, the total assets held on domestic accounts were approximately equal to the US GDP). These assets predominantly come from abroad, which makes Switzerland the world's largest offshore financial center. Roughly speaking, Swiss bank accounts contain a third of the world's financial wealth that is held abroad (Straumann 2006, 139; Wetzel, Flück, and Hofstätter 2010, 352; Zucman 2016).
With the consent of Swiss Bank, I was taking part in the day-to-day work life of the bank's financial analysis department, a large division of about 150 highly educated and well-paid employees. Financial analysts collect information and conduct analyses to understand current developments in financial markets. Then they valuate companies, business sectors, countries, and geographical regions to identify opportunities for investment. In so doing, they become powerful market actors. Their valuations and investment advice generate, increase, reduce, or cut short flows of capital. Companies can prosper if financial analysts see them as promising future investments. Countries can be flooded with foreign direct investment if analysts are positive about their future economic development. Similarly, analysts have the power to let companies and nations perish. Just think of countries such as Argentina or Greece, where "markets just could not wait," or of forced company restructurings caused by an "increase in market pressure." Financial analysts thus, to some extent, govern the economy. They take part in negotiating the value of companies, countries, currencies, and other entities that have been made investable and tradable in the current financial market economy.
It would, of course, be easy to see financial analysts as the only true holders of power in financial markets. But, as I learned during my time at Swiss Bank, the story is not that simple. Despite their influence, the role of financial analysts is challenged on two levels. First, doing financial analysis does not fit well with some of the key assumptions of economic theory. Economic theorists express a great deal of skepticism about whether it is possible to "beat the market," that is, to come up with specific forecasts that result in an investment strategy that performs better than the overall stock market. Since Cowles (1933), economists have argued that correctly forecasting market developments is more the result of chance than of straightforward calculation and expertise. And since the rise of Chicago-style neoclassical economics — today's leading school of economic thought — the claim that market movements can be predicted has been contested even more fiercely.
In the 1960s and 1970s, well-known economists such as Paul Samuelson, Eugene Fama, and Burton Malkiel popularized the critique of forecasting within the neoclassical school of economic thought. In his book A Random Walk down Wall Street, Malkiel ([1973] 1985, 16) stated that "taken to its logical extreme, it [the random walk] means that a blindfolded monkey throwing darts at a newspaper's financial pages could select a portfolio that would do just as well as one carefully selected by experts." Malkiel's provocative claim was based on Samuelson's and Fama's formulation of the efficient market hypothesis (see Fama 1965, 1970; Samuelson 1965). The efficient market hypothesis states that markets are informationally efficient, which means that expected changes in the stock price are so quickly reflected in the price that there is no room for financial analysts to forecast stock price developments for a longer period of time. As Fama says, the only way to forecast stock market developments in an efficient market is if a market participant possesses information that is not available to any other market participant. Since financial analysts cannot systematically access such insider information, neoclassical economists believe that the scope for predicting market developments is limited.
Second, the activity of financial analysts is significantly challenged by its empirical success or lack thereof. As I experienced during my time at Swiss Bank, financial analysts often fail to predict the correct future developments of financial markets. They fail to do so particularly because, even under the assumption that markets are not efficient, analysts still never know which elements of the information gathered will affect the financial market in what way. Scholars such as Working (1934), Kendall (1953), and Osborne (1959) empirically tested this issue of the analysts' uncertainty about future developments. They all came to the conclusion that, on average, financial analysts are largely unable to outperform the market.
This finding has been repeatedly illustrated not only in empirical finance studies, but also in the media. From 2003 to 2009, for example, the Chicago Sun-Times published annual stock market forecasts from "investment expert" Adam Monk. Adam was a capuchin monkey that, with a little help from his owner Bill Hoffmann, randomly pointed to five stocks listed in the financial section of a newspaper at the beginning of each year. The Chicago Sun Times later jokingly promoted these stocks as "investment advice." In 2006, after Adam Monk had impressively kept up with the overall market development and had even beaten many of his human colleagues, Jim Cramer, a well-known analyst with the television network CNBC, challenged Adam Monk. By also picking five stocks at the beginning of the year, Jim Cramer wanted to show how he — the star analyst — could outperform the monkey. He failed to prove his point: in 2006 and in 2008, the monkey managed to beat Cramer (performance tracked by Free by 50 2009). The same experiment was repeated in Great Britain, where Orlando, a ginger cat, outperformed human investors in 2012. Betting against a group of financial professionals and a group of novice students, Orlando generated the highest financial return of the three teams ("Investments" 2013).
Why Are There Financial Analysts?
The question that arises from these theoretical claims and empirical experiments is why there are financial analysts at all. In this book, I seek to explore the role of financial analysts and financial analysis as a market practice from an anthropological perspective. I am interested in how financial analysts act under conditions of uncertainty, how they construct their market forecasts, and how they become powerful market actors even if their practices are not plenary backed by economic theory and empirical success.
I argue that financial analysts establish and maintain their influential position in three ways. First, they are successful in presenting themselves as a group of market experts and, as such, as a distinct subprofessional category in banking. They distinguish themselves from other bankers by using cultural codes such as a particular language and style of dress and by referring to a particular body of acquired knowledge (see Boyer 2005, 2008). They thus acquire symbolic capital (Bourdieu 1984) that helps them to become recognized as a distinct and legitimate group of experts in finance. Second, by establishing market forecasts, analysts produce narratives that create a sense of agency in the highly unstable and uncertain field of financial markets. Their investment narratives allow investors to believe that, rather than being random, market movements can be understood through the work of financial analysts. Third, financial analysts are market intermediaries whose existence and activities are helpful to wealth managers and the host bank. By constructing investment narratives, they allow wealth managers to pass narratives on to investors. Also, analysts help the bank gain commissions by continually encouraging its clients to invest. Overall, I argue that all these factors help financial analysts transform the skepticism of economic theory and experienced failure into a powerful market position.
Throughout this book, I use the term "financial analysts" or "analysts" to refer to fundamental financial analysts in particular. Fundamental analysis is a market practice that aims to valuate stocks, bonds, and other financial market products on the basis of underlying financial data (such as a company's earnings, sales, or cash flow) and macroeconomic data (such as the development of interest rates or growth estimates). Fundamental analysts build on the assumption that analyzing financial and macroeconomic data can allow analysts to estimate a company's "intrinsic value," which, unlike its market value, contains all relevant information available to market participants and is not blurred by short-term biases (see Chiapello 2015, 19–20). By comparing the intrinsic value to the market value, analysts then predict future market movements. If the intrinsic value is higher than the current market value, analysts assume the stock price will rise (as information will eventually be reflected in the market value). If the intrinsic value is below the market value, analysts assume the stock price will fall (Bodie, Kane, and Marcus 2002; Copeland, Koller, and Murrin 2000; Zuckerman 2012).
Fundamental financial analysis is one particular style of doing financial analysis. Another style is technical analysis, sometimes also referred to as "chartism" (see Preda 2007, 2009; Zaloom 2003). Rather than looking at financial and economic data (financial analysts usually call them market fundamentals), technical analysts study the visual representation of the market price. Analyzing how the market prices of stocks, bonds, or other financial products develop over time, they try to recognize (visual) patterns that could give insights into how the price might develop in the future (see chapters 4 and 5 for detailed discussions of fundamental and technical analysis). What's important for now is that both fundamental and technical analysts lack legitimacy in neoclassical economic theory and experience failure in their everyday work. Their ways of dealing with failure, however, may be different. When talking about the construction of narrative strategies that help to overcome uncertainty, I am referring to fundamental analysis and not to chartism.
Financial Analysts and the Narrative Economy
I understand financial markets as a field in which single groups of market participants strive for influence and try to become members of respected subprofessional categories. This is, of course, not an entirely new approach. Since Marx, political economists have analyzed the economy as a field of political struggle. Similarly, economic anthropologists have long focused on the interplay between markets and power (see Hann and Hart 2011 for an overview). The "social studies of finance," however, an academic field that has inspired many of the studies to which I refer throughout this book, has so far paid little attention to the broader social and political role of financial experts. By highlighting the question of how knowledge is produced and circulated, scholars of the social studies of finance have predominantly examined financial market settings with a narrow focus on expert knowledge, rather than on how this expert knowledge becomes influential.
Many of the scholars investigating the relationship between knowledge and finance have adopted a particularly strong focus on the concept of performativity. Introduced by Michel Callon (1998), the term has been used to describe the framing of the economy (as a field) by economic theory. In his seminal article "What Does It Mean to Say That Economics Is Performative?" Callon (2007, 322) states, "To predict economic agents' behaviors, an economic theory does not have to be true; it simply needs to be believed by everyone." For Callon, the model of the market based on neoclassical economic assumptions — that is, efficient and entirely based on supply and demand — is not something that should be perceived as natural. Rather, it should be seen as a model that has become part of reality through an ongoing performative discourse, that is, a discourse that "contributes to the construction of a reality that it describes" (Callon 2007, 316; see also Muniesa 2014).
To illustrate the focal points of such performative effects, scholars from the social studies of finance usually refer to two empirical examples. The first one is Garcia-Parpet's (2007) study of the strawberry market. Garcia-Parpet studied the restructuring of a French strawberry market, in which an economic adviser had an enormous impact on reframing the market setting according to neoclassical economic theory. Through architectural and technological interventions, the strawberry market began working according to economic theory not because economic theory is a natural law, but because people structured the market according to the neoclassical paradigm. The second example is that of the Black-Scholes formula. As MacKenzie and Millo (2003) have shown, the invention of formulas such as the Black-Scholes formula — a mathematical formula used for option pricing — have had a significant impact on the pricing models used in financial markets. In contrast to Garcia-Parpet's strawberry case, performativity is not enforced by architecture, technological innovation, and consulting, but rather by a kind of nonhuman agency of economic models designed according to the neoclassical paradigm (for an overview of contributions to economic performativity studies, see MacKenzie, Muniesa, and Siu 2007).
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Excerpted from "Stories of Capitalism"
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