Peter Levin’s Rethinking Markets

Maligne Lake

Academic Identity

I am assistant professor of Sociology at Barnard College. My book (and my dissertation research) is a comparative study of technology and futures trading, an ethnography of open outcry and electronic traders. My current research is on how art specialists price cultural commodities, particularly how categories and commensuration work in the secondary/resale fine arts market. I teach courses in economic sociology, organizations, and gender.

Professional Identity

I occasionally consult, focusing on organizational change, the future of technology and financial markets, and environmental markets. I do strategic assessments of markets, technology and organizational design, with qualitative and quantitative components. If you are interested, please email me.

Personal Identity

I grew up outside Chicago, and went to school(s) at Wesleyan University, USC, and Northwestern University. I currently live in New York, with a partner who is a marketing manager for an educational nonprofit. I love movies, like to cook, and I can do a mean lindy swing out. I am INTP.


October 26, 2007

Markets and visualization

Filed under: Technology — Peter @ 5:37 pm

Daniel’s discussion of visualization is interesting, and it’s something I’ve had on my mind since reading Tad Williams’ Otherland series (the mysterious Mr. Sellars has a virtual garden that provides the GUI in an astoundingly complex virtual environment).

I think Daniel conflates two separate issues. The context is that market visualizations continue to be conservative, with the ubiquitous stock chart and even the ticker continuing to be the standards. This despite innovations all over the place in other kinds of visualizations.

The two issues, I think, are 1) what data should be contained in a market visualization; and 2) how might these visualizations be implemented into existing market trading praxis. The first is a question of information, and the second is a question of innovation, related but distinct.

So first, imagine two different visualizations, one a traditional chart that includes a set of quality measures that don’t traditionally make into market information (say, the number of times a firm’s CEO had family relations that week) and the other a new way of visualizing the same information everyone else uses. A good example of this second type is Bashiba (here’s a completely fascinating .wmv video link). Bashiba takes volume, volatility, prices, and maps them to the size of waves, the music, the weather. A listen and glance can tell you all the information at once.

visualization.jpg

What I think would be a disaster is to try to incorporate both at once. That kind of wholesale innovation is nice to think about, but wholesale revolution occurs less often than one might think, even (or especially) in finance.

So, the second part seems quite a bit like an institutional innovation problem to me. Normally, per someone like Clemens, the argument would go something like saying that innovation works if it is introduced within the currently agreed-upon form. So might seem like something new, but it is recognizable as something familiar. Particularly in the trading world, where for all the hoopla over the new masters of quant, many traders prefer three columns of numbers for buy-side, sell-side, and current trade, the recognizability has to be pretty immediate, and pretty accurate. A colleague, Brad Paley, makes his living making it possible for traders to learn the screen by “grabbing it with their eyes,” as one person describes it. He makes a good case for innovating by reproducing the familiar in new medium - not by copying a notebook electronically per se, but by making his handhelds enough notebook-ish that they are easily understood.

I’m not sure why Daniel believes that a ‘low-end entrant’ to the industry would lead the way in innovation - other than suggesting that innovations come from the outside, I’m not sure what the basis might be for that. I would think that innovation will come when traders recognize that the ‘new data environment’ actually gives them better means to act decisively than their old means. This suggests a generational shift in traders more than a low-end industry outsider.

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