By 2006, the combination of the SEC’s regulation, automated exchanges, algorithmic execution, high-frequency trading and dark pools made it possible for investors to trade stocks without intermediaries at the NYSE. A combination of economists, entrepreneurs and regulators had offered an alternative model: the exchange as a database. And in an important sense, their efforts appear successful: as microstructure economists like Hasbrouck and Saar (2010) have argued, spreads in the most-often traded indexes have narrowed following the introduction of Reg-NMS (see also Hendershott et al., 2011). In sociological terms, the automation enforced by the SEC can be read as an attempt to disentangle equities trading from the social relations between brokers and specialists. As someone told us at the NYSE, the SEC believed that the NYSE is more than an old “nothing boy’s network, a bunch of guys who take care of each other.” The SEC, with Lawrence Harris as its chief economist, were not unlike the chairman of the strawberry auction house described by Callon (1998): a reformer who found the relationship between market participants much to close for the proper functioning of the market. Indeed, there was a clear sense of technological optimism among industry participants in 2008. Automation would not only improve market structure, but also eliminate opportunism. For instance, according to Gregory Maynard, Systems and Product Strategy Director at electronic pioneer International Securities Exchange, automation would reduce behavior among traders to the explicitly permitted, eliminating ambiguity. According to him, On the floor there are all these rules that you’re not allowed to disobey. In the computer there are all these rules that you’re allowed to follow and nothing else. … The rules tell you what you do in the computer, they tell you what you do can can’t on the floor (Maynard interview; our emphasis). In other words, to Maynard automation was a form of better norm enforcement. This view is exactly the reverse as Lessig’s (2000): whereas Lessig warned about the risk of opportunism posed by automation, Maynard expected dubious manual practices to disappear in the process of translating norms into code. His argument for automation was not only about efficiency but a moral one.
By 2006, the combination of the SEC’s regulation, automated exchanges, algorithmic execution, high-frequency trading and dark pools made it possible for investors to trade stocks without intermediaries at the NYSE. A combination of economists, entrepreneurs and regulators had offered an alternative model: the exchange as a database. And in an important sense, their efforts appear successful: as microstructure economists like Hasbrouck and Saar (2010) have argued, spreads in the most-often traded indexes have narrowed following the introduction of Reg-NMS (see also Hendershott et al., 2011). In sociological terms, the automation enforced by the SEC can be read as an attempt to disentangle equities trading from the social relations between brokers and specialists. As someone told us at the NYSE, the SEC believed that the NYSE is “nothing more than an old boy’s network, a bunch of guys who take care of each other.” The SEC, with Lawrence Harris as its chief economist, were not unlike the chairman of the strawberry auction house described by Callon (1998): a reformer who found the relationship between market participants much to close for the proper functioning of the market. Indeed, there was a clear sense of technological optimism among industry participants in 2008. Automation would not only improve market structure, but also eliminate opportunism. For instance, according to Gregory Maynard, Systems and Product Strategy Director at electronic pioneer International Securities Exchange, automation would reduce behavior among traders to the explicitly permitted, eliminating ambiguity. According to him, On the floor there are all these rules that you’re not allowed to disobey. In the computer there are all these rules that you’re allowed to follow and … nothing else. The rules tell you what you can do in the computer, they tell you what you can’t do on the floor (Maynard interview; our emphasis). In other words, to Maynard automation was a form of better norm enforcement. This view is exactly the reverse as Lessig’s (2000): whereas Lessig warned about the risk of opportunism posed by automation, Maynard expected dubious manual practices to disappear in the process of translating norms into code. His argument for automation was not only about efficiency but a moral one.
Beunza_%20Folding.docx