سودمندی مدل های نادرست : به سوی درک ظهور مدیریت ریسک مالی

Is the growth of modern financial risk management a result of the accuracy and reliability of risk models? This paper argues that the remarkable success of today’s financial risk management methods should be attributed primarily to their communicative and organizational usefulness and less to the accuracy of the results they produced. This paper traces the intertwined historical paths of financial risk management and financial derivatives markets. Spanning from the late 1960s to the early 1990s, the paper analyses the social, political and organizational factors that underpinned the exponential success of one of today’s leading risk management methodologies, the applications based on the Black–Scholes–Merton options pricing model. Using primary documents and interviews, the paper shows how financial risk management became part of central market practices and gained reputation among the different organisational market participants (trading firms, the options clearinghouse and the securities regulator). Ultimately, the events in the aftermath of the market crash of October 1987 showed that the practical usefulness of financial risk management methods overshadowed the fact that when financial risk management was critically needed the risk model was inaccurate.

Financial risk management is one of the fastest growing service industries in the business world. According to the Global Association of Risk Professionals (GARP), one of the leading trade associations in the field, there are currently more than 74,000 financial risk managers in financial institutions.1 Dozens of academic and professional institutions award degrees and diplomas in financial risk management and these qualifications are gaining recognition by regulators and international certification bodies. At the heart of this body of knowledge and practices (virtually non-existent less than thirty years ago) is a set of financial economic theories, employing a variety of statistical models to assess and calculate the risks associated with a plethora of financial assets and contracts. Many of these financial risk management systems are proprietary and no reliable statistics are published about their use, but it is estimated that the daily transaction volume of financial products traded in organized exchanges that are managed using such methods exceeds 50 million transactions,2 with many more transactions executed in over-the-counter markets. Is this remarkable success an evidence of the predictive powers of modern financial economics? Judging from a brief review of several leading textbook in financial economics (Hull, 2005, McDonald, 2006 and Stulz, 2002), the answer to this question is a resounding ‘yes’: the accuracy and validity of risk models and the applications that use them are said to be tested and re-validated literally millions of times a day in the markets. In this paper we aim to show that such a representation is partial at best and that the explosive growth of financial risk management cannot be explained by the accuracy of the models and methods used. This paper traces the growth of financial risk management applications that made use of the options pricing model developed by Black and Scholes, 1972, Black and Scholes, 1973 and Merton, 1973, known as the Black–Scholes–Merton model. Arguably, this model is the crowning achievement of modern financial economics and was included in many of the pioneering financial risk management systems.3 The history of the Black–Scholes–Merton model is tightly connected to the first organized exchange for the trading of stock options, the American Chicago Board Options Exchange (CBOE). This historical case was studied previously (MacKenzie and Millo, 2003 and MacKenzie, 2006). However, while previous studies focused on the effect that the Black–Scholes–Merton model had on prices in options markets, this paper examines the development of financial risk management. The initial link between practice and model-based prediction is historical-temporal: CBOE began trading options less than two weeks before the mathematical model aiming to predict their prices, the Black–Scholes–Merton model, was published. These two coincident events mark the beginning of an exponential growth curve that traces both the markets for financial derivatives and financial risk management. This growth curve, we argue, was not fuelled simply by actors persuaded by the accuracy of the model. Instead, the usefulness of the model-based risk management, which enabled an efficient tackling of a variety of operational, organisational and political challenges, was a crucial factor behind the success of modern financial risk management. Model usefulness has three important organisational manifestations. First, model-based methods allowed clearer communication within trading organisations. It reduced the complexity of financial data and enabled more efficient decision-making (Sections ‘Risk assessment practices in early CBOE’ and ‘The rise of comprehensive risk management systems’). Second, applications based on the model solved the operational challenge of the clearinghouse when calculating the level of risk-based deposits required of traders (Sections ‘Financial risk management off the trading floor: options clearing’ and ‘Financial risk management as useful operational tools’). Third, the growing consensus among market participants around the usefulness of the model became useful in its own right when used by the SEC to legitimise its regulatory decisions (Section ‘Financial risk management and the 1987 market crash’). The accumulating effect of these different manifestations of usefulness contributed to a situation whereby the accuracy of the predictions it produced, even during critical times, was much less salient than one might expect. This approach, it has to be noted, does not aim to provide a definitive analysis of the emergence of financial risk management. Instead, it focuses on the interplay between technological, social and organisational factors and how it brought about the formation of rich interconnectedness among market participants.

As implied in the title of the paper, in many respects the story of the establishment of the Black–Scholes–Merton model simply marks the emergence of contemporary financial risk management. The current dominance of the risk management methods results in the fact that financial risk management is not limited only to financial markets, but to a variety of managerial decisions, from the amounts paid as equity-based bonuses to corporate executives to the degree of risk associated with exploring new oil fields, are taken in collaboration with systems that include variants of the Black–Scholes–Merton model. Can we draw a lesson from the history of financial risk management in early derivatives markets for other areas? Can a more general insight be derived from the specific historical case analysed in this paper? One possible direction is to examine the mechanisms through which knowledge dispersed from one realm of practice to another. The case shows that the small trading firms of early CBOE used model-based application (Fischer Black’s sheets) as a trading aid for the single traders. Then, when larger firms entered the options exchanges, model-based applications served as tools for organisational communication. The clearinghouse, in turn, developed a solution to a technical–operational problem using the model. Finally, the SEC approved an application that performed a regulatory function. This process of gradual dissemination of knowledge includes two elements. First, the transfer of knowledge regarding the Black–Scholes–Merton model was not simple diffusion of information, but was an interpretive process. The actors analysed the practices in which the model took part, ‘distilled’ from them the features that could be useful in their realm of practice and employed those feature in the new set of applications. These useful features of the model, the ‘bi-directionality’ of prices and quantified risks, were placed in a new techno-social set of conditions. However, the dissemination of knowledge related to the model included a second crucial element: the gradual accumulation of model-based technologies and practices, an accumulation that was not undermined by the realisation that the model was empirically inaccurate. Realising what the ‘active ingredients’ of the model were, was not, on its own, a sufficient condition for cross-realm adoptions of the model-based applications. It is true that market participants, such as the clearinghouse, tested the applications rigorously before they were put into service. However, it is unlikely that would have started the organisationally and politically costly process without strong indications from the trading firms that the model was useful for them. Similarly, the SEC would not have approved the model-based calculation of net capital with out having the clear realisation that both trading firms and the clearinghouse use it extensively. The combination of these two elements – the bare-bones ‘technical’ usefulness of the model and the social, emerging usefulness that derived from the fact that others also use it – is responsible for the widespread development and adoption of model-based applications. While a discussion about the efficacy of the first element, the inner structure of the model is beyond the scope of this paper, the strength of the ‘social usefulness’ is highly related to the fact that financial risk management emerged through a network of connections. The accumulation of implicit trust in the usefulness of the model, in spite of the different practices involved reminds of the phenomenon the American sociologist Burt (2005) defines as ‘closure’. Closure among two actors exists to the degree that the two have strong connections with other mutual actors and it tends to be positively correlated with the density of the network. When closure exists, the interdependency created through the structure of connections tends to bring about trust or at least trust-like effects. Accordingly, we can hypothesise that for a financial risk methodology to become successful and to spread across practice domains, the connections between the different actors need to be strong and the overall structure of connections has to be dense. This hypothesis implies the existence of a social–organisational structure of a very different nature from the one commonly assumed to exist in financial markets. While financial risk management is connected frequently with procedure-based, utilitarian, arm’s length type of connections, the development of financial risk management systems analysed here, when seen through the prism of Burt’s closure reveals a different type of dynamics: not only did the different organisational actors know each other well, but that they also trusted each other’s judgement about the usefulness of the systems. The development of practice-oriented trust across the different realms evokes another interesting theoretical concept that although not referring directly to the notions of accuracy and practicality, may still enrich our understanding about the historical process analysed in the paper. Bowker and Susan (1999) analyze classificatory systems and trace the ways through which these were embedded into organizational infrastructures and eventually became part of the taken-for-granted organizational reality. Using detailed case studies, Bowker and Leigh Star describe how the networks of connections both within organizations and among them created and legitimized rules and practices. They refer to the technical and procedural entities that bridged between the different organisational actors as boundary objects (although it may be better to refer to them as boundary-spanning objects). Boundary objects, according to Bowker and Leigh Star are objects that can facilitate communication among ‘several communities of practice and satisfy the informational requirements of each of them. Boundary objects are both plastic enough to adapt to local needs and constraints, yet robust enough to maintain a common identity across sites’ (p. 297). Thus, while not referring to accuracy issue, the concept of boundary object may help us to conceptualise the ways in which reputation about the model-based applications grew. The different market participants held widely varying perceptions with regard to risk, from which their different needs and constraint were derived. As the paper shows, financial risk management developed into such a ‘plastic’ medium that was able to accommodate different practices while allowing awareness about the common elements of the practices to evolve and strengthen the connections among the actors. Another area where the conclusions from this paper can be used as a basis for further conceptualisation is accounting research. The tension between accuracy and practice, inherent to the organisational application of expert knowledge, is highly relevant for accounting research. Whilst one of the fundamental principles of financial accounting, for example, is the production of accurate and objective reports, the very same reports are used to plan and bring about changes at the organisations described in the reports and thus affect the potential validity and accuracy of future reports. This constitutive power inherent to accounting is also related to the fact that accuracy is nested within the larger framework of relevancy and usefulness. Financial reports are aimed at various communities of practice (shareholders, prospective investors, creditors, etc.) and to be counted as accurate the data contained in the reports has to be relevant and useful to the particular group. Outside the group’s particular frame of reference, the question of accuracy has little meaning, as the sets of definitional algorithms with which the group measures the reports’ accuracy are embedded within the group’s practice-based epistemology (Brown & Duguid, 2001). This interplay between practices and accuracy begs the following question: if accuracy includes a fundamental practice-dependent dimension, then can the usefulness of a practice become a substitute for its lack of accuracy? For example, can a useful forecasting technique overcome the fact that the forecasts it produces tend to be inaccurate?26 These questions touch directly on the general question of nature of expert knowledge in and around organisations. As such, addressing these questions and analysing the processes that underpin them are central to the continuation of the project whereby accounting is conceptualised and understood as a social and organisational practice and in which the arenas where various aspects of this practice are mapped (Burchell & Hopwood, 1985). The conclusions of this paper, in turn, which analysed the emergence, ascendance and establishment of financial risk management techniques, build on this research agenda and offer to extend it, through further research, into areas that hitherto were virtually dominated by financial economics.