An Engine, Not a Camera: How Financial Models Shape Markets (Inside Technology)
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Winner, 2007 British International Studies Association’s (BISA) International Political Economy Group (IPEG) Book Prize. and Winner of the 2005 John Desmond Bernal Prize awarded jointly by the Society for Social Studies of Science (4S) and the Institute for Scientific Information.

In An Engine, Not a Camera, Donald MacKenzie argues that the emergence of modern economic theories of finance affected financial markets in fundamental ways. These new, Nobel Prize-winning theories, based on elegant mathematical models of markets, were not simply external analyses but intrinsic parts of economic processes.

Paraphrasing Milton Friedman, MacKenzie says that economic models are an engine of inquiry rather than a camera to reproduce empirical facts. More than that, the emergence of an authoritative theory of financial markets altered those markets fundamentally. For example, in 1970, there was almost no trading in financial derivatives such as "futures." By June of 2004, derivatives contracts totaling $273 trillion were outstanding worldwide. MacKenzie suggests that this growth could never have happened without the development of theories that gave derivatives legitimacy and explained their complexities.

MacKenzie examines the role played by finance theory in the two most serious crises to hit the world’s financial markets in recent years: the stock market crash of 1987 and the market turmoil that engulfed the hedge fund Long-Term Capital Management in 1998. He also looks at finance theory that is somewhat beyond the mainstream--chaos theorist Benoit Mandelbrot’s model of “wild” randomness. MacKenzie’s pioneering work in the social studies of finance will interest anyone who wants to understand how America’s financial markets have grown into their current form.

Customer Reviews:
  • Which came first, the market or the model?
    MacKenzie has an interesting take on the development of financial models, technology and organized exchanges, focusing on the latter half of the 20th century. He sees the three components as interacting as markets evolve. For example, the index futures exchanges did not really take off until options pricing theory made it possible to create spreadsheets to assist traders in options pricing. The incorporation of computers greatly increased market efficiency.

    MacKenzie analyzes the development of modern finance theory and its interplay with market evolution from a social-scientific, anthropological point of view. The people involved in the development of theory and markets take center stage; the author conducted dozens of interviews with academics and practitioners, and even reviewed the private papers of some. The amount of research incorporated into the analysis is impressive.

    One word of caution: although the book does not contain much math, and what is included is relegated to appendices, a strong familiarity with the development of financial models, at the level, say, of Bernstein's "Capital Ideas", would be greatly beneficial to one's enjoyment of this book.

    Summary: If you are interested in this topic -- read this book! You won't be disappointed....more info
  • A plausible case
    Many financial analysts and financial journalists have pointed to quantitative trading and the subprime mortgage markets as being the major cause behind the extreme volatility in the financial markets in the summer of 2007. This book therefore seems fitting for this particular time in financial history, if only at a bare minimum to educate the reader about the use of mathematical modeling in financial analysis and financial engineering. As the subtitle of the book indicates, the author's main thesis is that the use of mathematical models can actually change the dynamics of the markets themselves, moving them possibly to territories even more uncertain that they were invented to describe. Quantitative trading, now done by most of the major players in the financial markets, is dependent of course on mathematical modeling, some of which uses highly sophisticated reasoning patterns and artificial intelligence. Most of these models are proprietary, and therefore one cannot ascertain their efficacy in the acquisition of wealth for the organizations that deploy them. However, with a little pertinacity one can acquire a good understanding of their workings by studying the academic literature.

    Some of the predominant models in the public domain are discussed in this book, mostly from an historical perspective but the author inserts some of the relevant mathematics in its appendices for the more mathematically sophisticated reader. In general the author makes a plausible case for his main thesis, but at times his conclusions are based on mere anecdotes, and he makes the typical mistake of imputing power and influence to individuals that is unsubstantiated. It is very tempting, especially among those individuals or institutions that are involved in trading, or even responsible for innovations in the same, to believe that they are the cause for some of volatility in the financial markets. But such claims, even if they seem reasonable or intuitively clear, must be substantiated with careful statistical analysis, which can be time-consuming and difficult, and few individuals it seems are willing to devote themselves to such a project. The author though is aware of this, for he states very early on in the book that historical sources may not be sufficient to allow one to decide if the influences are real. In addition, he cautions the reader to "look not just at what participants say and write but also at whether the processes in question involve procedures and material devices that incorporate economics."

    The author labels the idea that economics as an academic project is actually part of economic processes the `performativity of economics', which he further breaks down into subclasses that serve to clarify the distinctions he wishes to make. One of these is more of a passive notion, called "generic" performativity, which is used to describe the participant's use of economic theories or data without emphasizing their effects on economic processes. If such effects take place, this is called "effective" performativity, which is then specialized to "Barnesian" performativity. The latter is used to describe the situations where the practical use of economic theory makes economic processes resemble what they are described to be by economic theory. Barnesian performativity is to be contrasted with `counterperformativity' where the actual use of economic models makes economic processes not resemble their description by these models. The author discusses how to detect Barnesian performativity, but warns of the difficulty in proving that movements in prices are following certain model predictions.

    But aside from the qualitative/historical emphasis that the author makes in this book and the small number of unsubstantiated claims of model-market influence, the reader will take away a better understanding of such topics as the capital asset pricing model, the Black-Scholes-Merton model of option pricing, the Modigliani-Miller theory of capital structure, a description of Levy processes and their role in econometrics, and most interestingly, a different explanation for the demise of Long Term Capital Management. All of these topics, coupled with the intellectual honesty and literary skill of the author, make this book a highly interesting contribution to the financial literature. ...more info
  • An Insightful Look into Finance's Twin Roles
    Both the science and the art and practice of finance have experienced phenomenal growth since the 1970s.

    As a science, finance has evolved from a descriptive outpost on the economic frontiers to become of that discipline's central topics. During the same period, the financial markets changed from what often seems today like sleepy outposts of liquidity into dynamic centers for financial engineering. In the 1970s, the world was being introduced to commodity hedging and options trading. By the early part of the 21st century, derivatives contracts totaling more than $273 trillion were outstanding worldwide.

    Donald MacKenzie, a sociology professor at the University of Edinburgh, argues in An Engine, Not a Camera, the trends are connected. Paraphrasing Milton Friedman, he argues the emergence of economic models were an engine of inquiry rather than a camera to reproduce empirical facts. As the science of finance became authoritative, the markets were altered. These new, Nobel Prize-winning theories, elegant mathematical markets models, were more than external analyses. They evolved into intrinsic parts of the financial process.

    Beginning with a discussion of the work of Franco Modigliani and Merton Miller, the Capital Asset Pricing Model and Random Walk, MacKenzie takes the reader on a journey through the development of the Black-Scholes-Merton model, The Crash of 1987, Long-Term Capital Management and the Russian government's default in 1998 to bind the threads of his thesis.

    Detailed, astute, well-written, and with much of the technical detail relegated to the appendices, this book weaves economics, financial theory, economic sociology and science and technology studies into an essential read for anyone with a serious interest in the financial markets....more info