The Handbook of Science and Technology Studies Part 14 pot

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Contemporary markets mean screens displaying an uninterrupted flow of prices in public places, financial products designed with the help of complex mathematical models, software programs for the instant display and analysis of financial data, and much more. Against the background of a global expansion, this massive presence, together with the growing dependence of financial transactions on both technology and formal modeling, raises the question of the impact of science and technology on a fundamental institution of modern soci- eties. The relevance of this question can be better understood if we take into account the historical dimension of the processes through which science and technology have penetrated financial transactions. Historians of economics and sociologists alike have recently acknowledged that this impact should be measured in centuries rather than decades (e.g., Sullivan & Weithers, 1991; Harrison, 1997; Jovanovic & Le Gall, 2001). How do they contribute, then, to the preeminent position occupied by financial institutions in developed societies? To what extent is finance shaped by science and technology? Since the mid-1990s, scholars from STS have become increasingly aware of these questions. Working initially independently of each other, several scholars started research projects on the role of science and technology in financial markets. The output of these projects has materialized in books, journal articles, Ph.D. dissertations, conferences, informal exchange networks, coordinated projects, as well as national associations (e.g., the Association d’études sociales de la finance in France). Research hosted at several universities in Western Europe and North America has grown at a steady pace, attracting doctoral students, research funding, together with the interest of academic publishers, and cross-fertilizing academic fields such as behavioral finance, economic sociology, economic anthropology, international political economy, and geography. One question arising here is that of the background against which the interest of STS scholars was directed toward finance. Several developments frame this moment, independently of particular interests and motivations. (1) After the fall of the Iron Curtain and toward the mid-1990s, the acceleration of global financial expansion 35 STS and Social Studies of Finance Alex Preda highlighted the central position occupied by technology and by formal models of finance. (2) More or less celebratory media representations of the wave of financial expansion contrasted with several severe crises toward the end of the 1990s, crises in which formal models played an important role (e.g., the Long-Term Capital Manage- ment crisis of 1998). These events triggered renewed discussions about the capacity of financial markets to replace social policies and raised issues of trust, legitimacy, and market constitution, directly involving both technology and financial theories. (3) Since the mid-1980s, criticism of the central assumptions of neoclassical economics had increased its pace in economic sociology as well as in the history of economics. Insights and theoretical approaches developed in science and technology studies had been fruitfully transferred to the history of economics, especially in the work of Philip Mirowski (1989). Additional research in the history of financial economics (e.g., Mehrling, 2005; Bernstein, 1996) also highlighted the conceptual links between physics (especially thermodynamics) and financial theory. Against this background, a transfer of research topics, concepts, and approaches from STS to the study of financial markets took place, to the effect that social studies of finance (SSF) emerged as a new field of inquiry. Yet, SSF (which comprises different emerging paradigms) cannot be seen as a mere extension or as an application of science and technology studies to finance. First, there has been cross-fertilization with other disciplinary fields, most notably perhaps with economic sociology. Second, SSF did not simply take over already existing STS concepts but modified and enriched them, developing its own research agenda. In the following, I discuss some of the most important conceptual and topical links between STS and the social studies of finance, thus exploring the SSF research agenda. In the first step of the argument, I show how various SSF approaches conceptualize the relationship between knowledge and finan- cial action, analogous to the STS conceptualization of the link between scientific knowledge and practical action. In a second step, I examine how SSF approaches the demarcation problem with regard to financial economics and to markets. I argue that the social studies of finance take over, reformulate, and expand the demarcation problem examined in science and technology studies. In the third step, I discuss the concept of agency developed in SSF and show its similarities and differences with con- cepts of agency present in science and technology studies as well as in economic theory. The conclusion reviews the research agenda of the social studies of finance and discusses potential cross-fertilization with the STS agenda. FINANCIAL INFORMATION AND PRICE AS EPISTEMIC THEMES Information has become a crucial concept of economic theory in the 1970s as a result (and continuation) of efforts started during World War II in operations research (e.g., Klein, 2001: 131; Mirowski, 2002: 60), efforts aiming at optimizing action outcomes based on random, incomplete data (e.g., tracking airplanes with guns and message encryption). This required mathematical tools for transforming randomness into determined patterns, tools that were combined with the notion (formulated by 902 Alex Preda Friedrich von Hayek and the Austrian School of economics in the 1930s) that markets can be seen as gigantic distributors of information, similar to a telephone switchboard (Mirowski, 2002: 37). This fusion between a view of allocation processes as determined by information on the one hand, and the formal processing of random signals in order to identify determined patterns on the other, led to conceptualizing information as additive signals, independently of the cognitive properties of the receiver. The effect was to separate information from cognition; while the former was treated as a sort of telephone signal, triggering a reaction from the receiver, cognition was deemed to be irrelevant. Noise was equated with uncertainty (Knight, [1921]1985) and seen as a blurring of determined (or meaningful) patterns, analogously to an encryption machine that scrambles the message by inserting (apparently) random signals. This concept of information as signals, which has proved influential in economic sociology too (e.g., White, 2002: 100–101) is being contested by the game-theoretical notion of information as choice of actions relative to signals under a fixed decision rule (Mirowski, 2002: 380). This introduces the idea of rational expectations on the part of economic actors (Sent, 1998: 22); expectations contain deterministic patterns that filter the random signals. This second notion of information maintains the dis- tinction to cognition, seen not as entirely irrelevant but as statistical inference. According to Mirowski (2002: 389; 2006), there is a third concept of information as symbolic computation, coming from artificial intelligence, which has proved less influential than the other two. Relevant in this context is the fact that “information,” as it is used in neoclassical economic theory, is seen analogously to phone signals. Uncertainty (or noise) is understood as random signals, with no underlying mean- ingful pattern, while cognition is taken either as irrelevant or as reducible to statisti- cal inferences. Financial markets can be seen thus as information processors, sending out price signals (Paul, 1993: 1475) on the basis of which actors make their choices according to (rational) decision rules. In this process, actors reciprocally anticipate their respec- tive expectations and incorporate them into signals. In turn, these anticipations are accompanied by dispersion and volatility, understood as a measure of ignorance and uncertainty in the marketplace (e.g., Stigler, 1961: 214). Along with price observation (Biais, 1993: 157), networks of relationships (e.g., Baker, 1984; Abolafia, 1996) and spe- cialization (Stigler, 1961: 220) contribute to reducing noise. Price signals are regarded as fully reflecting all the information available to market actors (Stigler, 1961). This is also a key assumption of the efficient market hypothesis (EMH). The presence of a large number of actors in the market, acting independently of each other, handling all the relevant information they can get, is a fundamental condition for market efficiency and liquidity (Fama, 1970, 1991; Jensen, 1978). These participants “compete freely and equally for the stocks, causing, because of such com- petition and the full information available to the participants, full reflection of the worth of stocks in their prevailing prices” (Woelfel, 1994: 328). EMH is related to the random walk hypothesis (RWH), which can be followed back to Louis Bachelier’s treatment of stock price movements as a Brownian motion STS and Social Studies of Finance 903 ([1900]1964) and to Jules Regnault, a mid-nineteenth-century French broker (Jovanovic & Le Gall, 2001). Prices are conceived of as similar to gas molecules, moving independently of each other, with future movements being independent of past move- ments. This tenet grounds models for computing the probability of future price move- ments, such as the Black-Merton-Scholes formula (Mehrling, 2005; MacKenzie, 2006). The EMH tenet was contested early by Benoit Mandelbrot, who noticed that price fluc- tuations are inconsistent with a Gaussian distribution of securities prices (they gener- ate “fat tails”) and that prices are scale-invariant (Mirowski, 2004: 235, 239: Mehrling, 2005: 97–98). The assumption of market efficiency presupposes that at any given time economic agents can distinguish between (meaningful) signals and noise, between the relevant and the irrelevant, without recourse to issues of cognition. Several epistemological problems arise here. (1) The distinction between prices and price data: prices as signals cannot be separated from price data, which are not neutral with respect to produc- tion and recording processes, as well as to their material support. Recording data implies the use of technology; therefore, the question arises about how price record- ing technologies shape price data and financial transactions with them (see the Social and Cultural Boundaries of Financial Economics section). (2) The generation and recording of data are not independent of formal and informal theoretical assumptions about veridicality, consistency, homogeneity, reproducibility, comparability, and memorization, assumptions that are incorporated into recording procedures and tech- nologies and reflected in analysis and interpretation. How are these assumptions pro- duced, and which social forces are involved in this process? (3) The use of price data by financial actors implies observation, monitoring, and representation. These processes, in their turn, require interpretation (provided by financial theories), skills, and tacit knowledge. Seen in this perspective, price data neither appear as given, natural, or determined by the inherent rationality of financial actors, nor do they appear as analogous to phone signals that trigger the recipients’ reactions. Rather, these data appear as prax- eological structures (Lynch, 1993: 261), that is, as routine, accountable sequences of social action. In this perspective, information, the key concept of financial econom- ics (Shleifer, 2000: 1–3), is not treated as the natural starting point of investigation but as a practical problem for financial actors. When using price data, academic econ- omists share a set of epistemic assumptions with nonacademic financial actors: assumptions about veridicality, consistency, homogeneity, reproducibility, and so on. The scientific work of financial modeling or experimenting does not appear as embed- ded in a type of understanding or rationality radically different from (and superior to) the lay one. At the same time, since theoretical models are used in financial transac- tions, they have not only a representational but also an instrumental quality. How do they affect, then, the very assumptions they rely on? A first task on the research agenda is, therefore, to investigate these price-related epistemic themes. I begin with price observation: what does it mean to observe securities prices as objective and given? Karin Knorr Cetina and Urs Bruegger have studied how dispersed 904 Alex Preda [...]... and from their activities, and thus the rate of such atmospheric change Nature and the Environment in Science and Technology Studies 929 depends on the speed and nature of economic growth, the size of future populations, the technologies chosen by people, the cultures of consumption and leisure they develop, and so on The institutional assumption of the IPCC is that the only relevant social science. .. extension and modification of the notion of agency developed in the sociology of science and technology Another example is the concept of markets as a reflexive system, built on an analogy with the concept of laboratory This indicates growing disciplinary autonomy, without affecting the ties between STS and SSF Owing to the close personal and intellectual ties between these fields, I expect them to stay... on the concept of performativity and influenced by (but not limited to) the actor-network theory perspective and another one grounded in the tradition of laboratory studies and centered on field work in the trading room I expect that further empirical studies and theoretical contribution will deepen the differentiation process In any case, the prominence of financial institutions in our world, together... aspects of the issues Correspondingly, other STS work has focused on the role of the social sciences in analyzing climate change and, to some extent, on the IPCC’s own social science Though, according to the self-understanding of the IPCC, these disciplines could not have the precision and exactitude to which the physical sciences aspired, it was clear that global climate change could not be studied in the. .. trading programs; (3) the effects of technology on the organization of financial exchanges and the perception of financial data; and (4) the ties between technology and forms of financial expertise like securities analysis With respect to the first issue, recent historical studies have shown that, when the first price-recording technology (the stock ticker) was introduced on the NYSE, user and producer groups... Callon, Michel (1999) “Actor-Network Theory: The Market Test,” in J Law & J Hassard (eds), ActorNetwork Theory and After (Oxford: Blackwell): 181–95 Collins, Harry M & Robert Evans (2003) The Third Wave of Science Studies: Studies of Expertise and Experience,” Social Studies of Science 32(2): 235–96 Davis, John B (2003) The Theory of the Individual in Economics: Identity and Value (London: Routledge) Dimson,... the Environment in Science and Technology Studies Steven Yearley KNOWING NATURE In the decade since the first STS handbook to include a chapter on the environment (Yearley, 1995), the significance of environmental topics to the science and technology studies community has grown with startling rapidity In part this is because there has been an increasing number of detailed studies on topics such as environmental... within the IPCC (for an analysis of the accusations that could be leveled, see P Edwards and Schneider, 2001) In line with the classic script of science for policy,” the IPCC legitimated itself in terms of the scientific objectivity and impartiality of its members But critics were able to point out that the scientific careers of the whole climate change “orthodoxy” depended on the correctness of the underlying... rational and nonrational behavior, gambling and investing, human actors and prices) that lay the ground for the formal theory of efficient markets 908 Alex Preda Although the prehistory of financial theory traced these cultural and conceptual boundaries, the theory’s growth into a full-blown deductive, formal model took place between the 1950s and the early 1970s The more general intellectual background of. .. (1) about financial theory as the product of a historical development and about the social and cultural factors playing a role here, (2) about how the boundaries of this model were drawn, and (3) about the relationship between the theoretical model and the empirical data against which it is tested The historiography of economics has presented modern financial theory as the result of a straightforward . argue that the social studies of finance take over, reformulate, and expand the demarcation problem examined in science and technology studies. In the third step, I discuss the concept of agency. assumption of the efficient market hypothesis (EMH). The presence of a large number of actors in the market, acting independently of each other, handling all the relevant information they can get,. SSF and show its similarities and differences with con- cepts of agency present in science and technology studies as well as in economic theory. The conclusion reviews the research agenda of the