Comments on: Intermediaries and Ambiguity http://www.rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html Economic Sociology from the Ground Up Fri, 30 Sep 2011 15:24:01 +0000 hourly 1 http://wordpress.org/?v=3.3.1 By: Andrew http://www.rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html#comment-14 Andrew Tue, 21 Aug 2007 11:42:33 +0000 http://rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html#comment-14 Thanks for the clarification. I should have recognized the point from March. Finance and economics are far beyond my ken, but my elementary understanding of prices is that it's a way of not only observing positions in a market but 'getting' observations in turn (in an almost Leiferian sense). So, if there is total darkness it raises the question of whether it's a matter of not being able to see, or not being able to be seen, and why. Thanks for the clarification. I should have recognized the point from March. Finance and economics are far beyond my ken, but my elementary understanding of prices is that it’s a way of not only observing positions in a market but ‘getting’ observations in turn (in an almost Leiferian sense). So, if there is total darkness it raises the question of whether it’s a matter of not being able to see, or not being able to be seen, and why.

]]> By: Peter Levin http://www.rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html#comment-13 Peter Levin Tue, 21 Aug 2007 08:09:58 +0000 http://rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html#comment-13 Good point, and let me try to clarify. More theoretically, this owes major debt to James March. His argument is (in part) concerned with decision-making. Uncertainty is something like saying, we know what our preferences/goals are, and there are lots of different paths to get there - what is the best path? You can reduce uncertainty (perhaps) with additional information, to get to an ideal decision. Ambiguity is more like saying, even our preferences are unstable and we don't know them; any of these paths are likely to change both our likelihood of getting there, but might also change the goal itself. So additional information is actually not going to solve the problem. Instead, we need to make enough things stable in order for ambiguity to be transformed into uncertainty, from where we might be able to move towards optimal solutions. Now, for March, what's interesting is that the world is ambiguous, and the best we can do is move forward and be flexible. For my purposes, the categories, commensuration, etc., is all work that gives enough stability of some things (criteria for evaluation), so that you can have movement of other things (price). An interesting example is happening with regard to finance right now, and some of the market meltdown per mortgages and quantitative finance. Pablo Triana hits it on the head <a>here</a>: <blockquote>But what about math finance? Surely, quants out there must be at least a bit curious about a market where the price not just can dive to zero, it can actually dive into nothingness. No price at all. Nothing. Total darkness. We are not talking about zero value, but unknown value. During the LTCM crisis, valuing long-dated equity index options became difficult becacause the number of players was so small, but at least here implied volatility came to the rescue. All it took was to input a never-seen-before artificial 40-45% figure for implied vol. These days, things don´t appear that easy. Several i-banks and funds simply don´t know what some of their credit positions are worth. Those of the modelling variety might be puzzled by this unruly reality. Hey, my computer can churn out a price! Yes, but who is buying? The possibility that for certain assets no value at all may be obtainable for a while in case of a liquidity crisis is certainly a quanty challenge. </blockquote> I think the 'total darkness' is interesting, and he suggests that plugging in hypothetical numbers is not even possible at this point. It's not totally parallel, but it captures some of what I'm thinking about. Good point, and let me try to clarify. More theoretically, this owes major debt to James March. His argument is (in part) concerned with decision-making. Uncertainty is something like saying, we know what our preferences/goals are, and there are lots of different paths to get there – what is the best path? You can reduce uncertainty (perhaps) with additional information, to get to an ideal decision.

Ambiguity is more like saying, even our preferences are unstable and we don’t know them; any of these paths are likely to change both our likelihood of getting there, but might also change the goal itself. So additional information is actually not going to solve the problem. Instead, we need to make enough things stable in order for ambiguity to be transformed into uncertainty, from where we might be able to move towards optimal solutions.

Now, for March, what’s interesting is that the world is ambiguous, and the best we can do is move forward and be flexible. For my purposes, the categories, commensuration, etc., is all work that gives enough stability of some things (criteria for evaluation), so that you can have movement of other things (price).

An interesting example is happening with regard to finance right now, and some of the market meltdown per mortgages and quantitative finance. Pablo Triana hits it on the head here:

But what about math finance? Surely, quants out there must be at least a bit curious about a market where the price not just can dive to zero, it can actually dive into nothingness. No price at all. Nothing. Total darkness. We are not talking about zero value, but unknown value.

During the LTCM crisis, valuing long-dated equity index options became difficult becacause the number of players was so small, but at least here implied volatility came to the rescue. All it took was to input a never-seen-before artificial 40-45% figure for implied vol.

These days, things don´t appear that easy. Several i-banks and funds simply don´t know what some of their credit positions are worth.

Those of the modelling variety might be puzzled by this unruly reality. Hey, my computer can churn out a price! Yes, but who is buying?

The possibility that for certain assets no value at all may be obtainable for a while in case of a liquidity crisis is certainly a quanty challenge.

I think the ‘total darkness’ is interesting, and he suggests that plugging in hypothetical numbers is not even possible at this point. It’s not totally parallel, but it captures some of what I’m thinking about.

]]> By: Andrew http://www.rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html#comment-12 Andrew Mon, 20 Aug 2007 23:12:27 +0000 http://rethinkingmarkets.org/2007/08/18/intermediaries-and-ambiguity.html#comment-12 I would say that a 'sociology of the invisible' is as compelling a way of identifying a number of practices and arrangements that are integrated into and embedded within a diversity of institutionalized contexts and not just markets (my own field is education and health studies). As you say, they get short shrift because they are boring - boring, that is, until they 'inexplicably' fail, like infrastructure. So thanks for this observation, which crystallized some thoughts I was only able to express inchoately until now. Still, I'm a little confused when you write: "They are, as a number of us in this area have said, the sociology of the invisible, the infrastructure, the boring. Accounting systems, valuation, categorization, these are things which reduce ambiguity to a sufficient degree that we can have uncertainty." For the uninitiated and unsophisticated (that's me), the distinction between uncertainty and ambiguity you're drawing here is subtle, so I was wondering if you'd provide clarification. Ambiguity appears to be a type of situation where commensurability of objects/practices, etc. isn't even established, so that we don't even have stable entities about which to be certain or uncertain. Is that it? So here we're dealing with ambiguity as a very specific type of uncertainty? I would say that a ‘sociology of the invisible’ is as compelling a way of identifying a number of practices and arrangements that are integrated into and embedded within a diversity of institutionalized contexts and not just markets (my own field is education and health studies). As you say, they get short shrift because they are boring – boring, that is, until they ‘inexplicably’ fail, like infrastructure. So thanks for this observation, which crystallized some thoughts I was only able to express inchoately until now.

Still, I’m a little confused when you write:

“They are, as a number of us in this area have said, the sociology of the invisible, the infrastructure, the boring. Accounting systems, valuation, categorization, these are things which reduce ambiguity to a sufficient degree that we can have uncertainty.”

For the uninitiated and unsophisticated (that’s me), the distinction between uncertainty and ambiguity you’re drawing here is subtle, so I was wondering if you’d provide clarification. Ambiguity appears to be a type of situation where commensurability of objects/practices, etc. isn’t even established, so that we don’t even have stable entities about which to be certain or uncertain. Is that it? So here we’re dealing with ambiguity as a very specific type of uncertainty?

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