I am in awe of how much a group can accomplish, if there is one dedicated member who works hard without protest nor attention need. People flock to help him out. I see it frequently in markets and our Scout troop. It also works in the opposite direction, unfortunately. I wonder how to quantify that individual… Atlas if you will… who drags others along by strength without yelling. It's also in the markets, but I can't get a handle around how to quantify the lack of need for attention. Singleton played this game masterfully at Teledyne. Yes there are generals, but how do you define the majors that actually embarrass them (and others below them) into bravery?

 George Parkanyi responds:

Why would you even want to quantify such an individual? Quantifying andcounting isn't everything. Some people are just a life force, and you knowit because you can't help but recognize it as soon as you meet them or seethem in action. These people are so effective because they point the way to possibility,fire the imagination, and scoff at obstacles as mere details. And othersthen follow because who wouldn't want to be part of something that isunique, infused with energy, and helps define them in some special way?Everyone wants meaning in their lives. Show people how to create it andthey (well at least some) will rise to it. Also, not everyone has a clearsense of where they want to go, or if they do, haven't figured out how toget there. Give them an interesting destination, and/or a plan, and they'lloften be more than happy to throw in time, effort, and resources and goalong for the ride or even better, adventure.





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1 Comment so far

  1. douglas roberts dimick on November 13, 2009 1:52 am

    Jeff, that issue of quantifying “the lack of need for attention” was one that I pondered – relative to defining and then quantifying electronic exchange market behavior a la patterning – in 2002 when formulating a statement of theory for SMART.

    My inquiry began with that, your title, whereas it might be considered a term of art in law and rhetoric. Moreover, my development of the Theory of Quantitative Relativity (or QR) has rules-based applications for program trading systematic designs, so fallacies of logic become a central consideration.

    As a potential characterization of market behavior, I posit that the “slippery slope effect” is unquantifiable as a continuum fallacy. Consider Sorties paradox ( relative to volume and price formulations of a given security during a continuum of electronic market transactions (long and/or short) occurring on a sanctioned exchange…

    For example, when there is a long trade and then subsequent short trade followed by a sequentially designated time period of assimilated (or price-effected [up or down]) exchanges, whereby there is a discrete progression of (again, for example) increasing/decreasing liquidity or frequency of those corresponding, directional transactions, could rules-based functions correlate that continuum of price movement – perhaps defining day, swing, or trend indications – as states (or statistical domains)?

    An excerpt from my (QR) statement of theory: “Psychology of the masses can be further influenced by an evaluation of risk versus reward. Each market participant determines if the reward of the investment is worth the risk of loss, possibly evaluating the expected reward for the investment. This determination then provides an influence defining the strength or weakness of the energy flow leading to the duration of the momentum. Further, this flow of energy is then compared relatively to the performance of the market, the industry sector, and to the security itself with regards to its own price action. Finally, the Light Velocity (c) variable is replaced …”

    From this, we may theorize as to quantification, “wherefrom…

    P = a + b = (c + d)e

    1. Psychology is result of energy either positive or negative as determined by influences:

    a. Action plus reaction energy (price and volume)
    b. Balance or power equality or direction of flow (wave or trend)
    c. Risk and reward cycles and proximity to support/resistance (price)
    d. Strength or weakness load factor related to current/historical (volume)
    e. Duration of momentum time of variables from junction (1/3/5minutes)
    f. Compared to price action market, industry, stock price action (beta)

    2. Momentum is energy flow as determined by influences:

    M = g + h

    g. expectation of risk and reward cycles and proximity to support/resistance levels (price)
    h. relative strength or weakness load factor related to current/historical (volume)
    i. time sequential (duration of direction per DA/fd)”

    Of course, these semantics return us to the fallacy as to whether two states can be consider distinct, because they exist (theoretically, given our example) within a transactional continuum (or as such a measurement being defined by domains of time or trades). This problem is compounded by the fallacy’s condition precedent that “differences in quality cannot result from differences in quantity” (

    Now we circle back to Sorties paradox with the heap of sand analogy. Is there still a heap if one grain of sand is removed – or only one grain remains?

    In our example, if price movement presents a directional continuum (up or down) while convergence and divergence of functional indicators of liquidity/frequency evidence contra/confirm-like indications, then may we say that a quantifiable patterning exists “relative” to the initial, two (long and subsequently concurrent short) trades?

    The Theory of Quantitative Relativity says “yes” – that a rules-based logic may be constructed. To quantify the “relativity” of price action, codification and systematic identification of such patterning equates the ecology of (non)directional electronic exchanges to the variables of space and corresponding time(s) correlative to energy.

    As one of a number of examples to be found a daspec, Victor’s “Repetition of Parts” and my comment glimpse at how subsequent formulations may then progress, whereby “[o]utput would determined by defined state-input-state parameters” ( ).



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