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An Engine, Not a Camera: How Financial Models Shape Markets

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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 e 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.


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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 e 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.

30 review for An Engine, Not a Camera: How Financial Models Shape Markets

  1. 5 out of 5

    Sarah

    In many ways I've modeled my dissertation after this book. It's contemporary economic sociology at its best, I think. In many ways I've modeled my dissertation after this book. It's contemporary economic sociology at its best, I think.

  2. 5 out of 5

    John Farr

    This is a wonderfully informative book on the history and sociology of financial theory. The author shows a great command of the subject matter, which I found impressive as he is a sociologist by training. The big idea of this book is that the models that financial theorists introduce to their MBA students (Black-Scholes, CAPM, etc.) end up impacting the prices of the very securities that they are supposed to value. In this way, finance practitioners mistake these models as being a "camera" that This is a wonderfully informative book on the history and sociology of financial theory. The author shows a great command of the subject matter, which I found impressive as he is a sociologist by training. The big idea of this book is that the models that financial theorists introduce to their MBA students (Black-Scholes, CAPM, etc.) end up impacting the prices of the very securities that they are supposed to value. In this way, finance practitioners mistake these models as being a "camera" that is used to mistakenly assess the world than an "engine" used to understand how markets operate. MBAs then use the snapshots from this "camera" in order to force prices of different securities in line with what the models suggest they should be. This can result in systemic mis-pricings and other problems. MacKenzie does an impressive job of teasing out the implications of this through extensive research and interviews with academics and practitioners. The book reminded me of an updated version of Bernstein's "Capital Ideas," a history of financial theory that came out some time in the 80's. MacKenzie is more academic and draws more heavily on sociological theory, but it makes the text no less readable, in my opinion. Strongly recommended for anyone interested in finance.

  3. 4 out of 5

    Krishaan Khubchand

    i’m still dipping in and out of this book, but i’ve been thinking a lot about the almost cyborg-construction of economic agents IRL and this quote from Glen Weyl’s twitter: ‘I've been going over how strange and fundamentally anti-technological and radically conservative the whole framing of mainstream economics is. After all, economic systems are basically information and communications tech. Essentially ways of transmitting information about human value and identity over long distances...somethin i’m still dipping in and out of this book, but i’ve been thinking a lot about the almost cyborg-construction of economic agents IRL and this quote from Glen Weyl’s twitter: ‘I've been going over how strange and fundamentally anti-technological and radically conservative the whole framing of mainstream economics is. After all, economic systems are basically information and communications tech. Essentially ways of transmitting information about human value and identity over long distances...something widely understood in the field. And yet the whole field is built around the notion that some system roughly approximating those prevalent today is "optimal" and that any deviations from this are weird "market failures". Compare this to any other area of ICT and it just seems totally bizarre. Imagine that in the late 19th century people assumed that the telegraph basically captured all one could hope for from ICT and all that was left were tweaks to get it "just right"...or what would AI be like if we assumed that existing computers basically were the human mind, up to some fine tuning.” — I was reading parts of Joel Mokyr’s Lever of Riches this morning and it struck me that this was one of the few case studies where you see the economic impact of technology in day to day action, as agencements/enhancements. Looking forward to continuing to read!

  4. 5 out of 5

    Stanisław

    A lot of economic sociology tends to lament the mathematization of economics without really assessing the usefulness of math applied and to dismiss its models on the grounds of its unrealistic assumptions, shouting with a revelatory passion that the homo economicus does not really exist (you don't say), juxtaposing the rigid, rational worlds of economics and "irrational" embeddedness of the social. In contrast, MacKenzie goes to great length to understand the models, which history he's discussin A lot of economic sociology tends to lament the mathematization of economics without really assessing the usefulness of math applied and to dismiss its models on the grounds of its unrealistic assumptions, shouting with a revelatory passion that the homo economicus does not really exist (you don't say), juxtaposing the rigid, rational worlds of economics and "irrational" embeddedness of the social. In contrast, MacKenzie goes to great length to understand the models, which history he's discussing and approaches the field charitably. He also shows that the social and the rational are not two opposable logics, but that the social can often be acomodative and facilitative of the formal models employed by economists. The book treats the subject matter in a very extensive way which makes it quite long. I suppose that the chapter on Mandelbrot could easily be a footnote.

  5. 5 out of 5

    Daniel

    Oh my lordy. What a book. Who knew such simple models would have such profound effects. Inspirational. I'd write a proper review but I'm watching Vertigo and Scottie is under trial. Oh my lordy. What a book. Who knew such simple models would have such profound effects. Inspirational. I'd write a proper review but I'm watching Vertigo and Scottie is under trial.

  6. 4 out of 5

    Rob

    So good

  7. 5 out of 5

    Anthony

    Explains rather well how the Chicago neo-classical models came to dominate finance and how these models became self-fulfilling prophecies.

  8. 5 out of 5

    James Goldstein

  9. 4 out of 5

    Qiang Liu

  10. 5 out of 5

    Adam

  11. 5 out of 5

    N P Pollock

  12. 4 out of 5

    Allan Olley

  13. 5 out of 5

    Adam Elkus

  14. 4 out of 5

    Gary Robinson

  15. 5 out of 5

    Tari

  16. 5 out of 5

    Michael Roytman

  17. 5 out of 5

    Bill Mill

  18. 5 out of 5

    Rafael Marques

  19. 5 out of 5

    Richard Familetti

  20. 4 out of 5

    Gabor Scheiring

  21. 5 out of 5

    Antti S

  22. 5 out of 5

    I-Hsuan Hsu

  23. 5 out of 5

    John

  24. 5 out of 5

    Adam Burke

  25. 4 out of 5

    Adam

  26. 4 out of 5

    Glenn Bridgman

  27. 5 out of 5

    Donald Steiny

  28. 5 out of 5

    ARK

  29. 5 out of 5

    Tim Gebbie

  30. 4 out of 5

    Fredrik

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