What Bohm Saw
The relationships between things are part of what the system is
Next: Episode 2, The Future Is Not Hidden, It Is Unwritten
A risk report shows each futures position within its intended limit. Then a common move sends several markets against the account together. The rows were accurate, yet the portfolio loss feels like a violation of what they said. The risk had been present in their arrangement all along.
Look up from the report to the birds in this episode’s image. Thousands of starlings gather above a dark landscape. No bird commands the shape that folds through the flock. Each moves in relation to others nearby. Branching channels of water lie below, formed by different forces. Both pictures invite us to study the organisation among their visible parts.
The portfolio’s individual trades are real, just as each bird is real. I need to know how a contract was sized and filled. I also need to know what several positions will do together if a shared constraint calls them to exit at once. David Bohm’s language of visible and underlying order helps me hold those questions together, but the financial mechanism still has to be found in orders, capital and price.
The useful cut and what it leaves out
Analysis begins by drawing a boundary. A scientist measures a bird’s speed or its distance from a neighbour. A trader records an entry price, a contract, a position and an exit. Those cuts are useful. If an order has been placed at the wrong size, an appeal to wholeness will not correct it.
But the cut changes what we can see. The starling’s movement at one instant is partly a response to other starlings. Its next surroundings depend on the flock they are jointly forming. Cavagna and colleagues measured long-range correlations within starling flocks, an empirical reminder that the collective pattern is more than a picture imposed by an observer at a distance. [1] The birds are real. So is their organisation.
Four findings recur in the study of complex adaptive systems. First, responses can be non-linear. Doubling a change in one input need not double the result, particularly near a threshold. Second, emergence describes behaviour at the level of the group that no single member carries by itself. Third, feedback returns the consequences of an action to the actors who made it. Fourth, path dependence means the sequence of earlier events helps determine what is possible now. These are not four mysterious forces. They are features we can investigate in a particular system.
Non-linearity is familiar to anyone who has tried to leave a crowded trade. Selling another contract when many buyers are waiting may barely move the price. Selling it when bids have vanished can matter enormously. The size of the order has not changed; the surrounding market has. That is why a position scaled sensibly to recent movement can still encounter a loss quite unlike the ordinary observations used to scale it. The response belongs to the configuration in which the order arrives.
Emergence appears when the assembled behaviour has properties that cannot be located in one part. No starling contains the shape of the flock. No individual order contains a day’s market trend. The large pattern is produced through local actions and becomes part of the circumstances in which later local actions take place. Naming it does not mean we have abandoned the birds or the orders. It directs us to ask how their interactions generated something we could not describe from one alone.
Feedback gives this pattern its movement. A rising price attracts some traders and drives others to cover a short. Their orders may extend the move, inviting further responses. In another setting the same rise may attract selling and die out. Positive and negative feedback can both occur, and their balance can change. If I identify a trend solely by its earlier price path, I leave out the possibility that its continuation depends on which responses that path now elicits.
Path dependence gives the system a memory without asking us to imagine a literal memory stored in a market. Positions accumulated earlier, capital already committed and losses already incurred affect which actions are feasible now. Two markets can reach the same price through different histories and meet different orders at that price. Likewise, two traders with identical rules but different recent return paths may have different capital and mandates with which to execute them. The present is not just a set of numbers. It carries the consequences of the route by which it arrived.
What Bohm named
Bohm was a physicist dissatisfied with a worldview that treated apparently separate things as the basic units of reality. In Wholeness and the Implicate Order, the explicate order is the world that appears to us as distinct objects, events and measurable variables. The implicate order names a deeper order of mutual constitution from which that visible order unfolds. [2] In this series I use the latter as a way of thinking about a constraint structure: the relations that make some configurations possible and others unable to persist. We cannot see that entire structure directly from inside a changing system. We infer parts of it from what appears and from how it changes.
Bohm offered a physical illustration. A drop of insoluble ink in a slowly stirred viscous fluid can be drawn into an exceedingly fine thread. The drop vanishes from ordinary sight, then becomes visible again when the stirring is reversed. The ink was neither destroyed nor created in the reversal. Its visible form depended on an order distributed through the fluid. The demonstration helps us imagine enfolding and unfolding, although a market does not operate like a cylinder of glycerine (see Figure 1). [2]
Figure 1. When drops of food colouring are added to this fluid and mixed, the colours blur, yet reversing the rotation unmixes them. [3]
The appeal of Bohm’s vocabulary is that it gives a name to a recurrent mistake. We see an explicate price series and treat it as though its measured variables were the market itself. We see a stable-looking correlation and forget the participants, financing arrangements and common constraints under which it was produced. When those relationships shift, the numbers can be recalculated perfectly while their old interpretation fails.
The distinction is not a licence to posit an invisible cause whenever a model disappoints. Bohm’s account of physics remains debated. Market observations do not establish his quantum theory, and the language of implicate order is a lens rather than a substitute for specifying a causal mechanism. The claim I will defend is narrower and substantial: in an adaptive market, relationships and feedback belong in the explanation of what its measured parts do.
The observer is already inside
Why are separate parts so persuasive to us? We are embedded observers. At a trading desk, I must look at one price, then another, choose an order, check a fill and keep a record. The instruments available to me and the decisions I must make present the market as discrete things. Reductionism makes that inside view rigorous. It turns passing experience into observations that can be compared, challenged and corrected.
That is a strength. It is also a position with a horizon. From inside a market I cannot observe all the expectations forming elsewhere or every effect of the orders I send. My model is made from a record of interactions, and its use may enter the next interaction. I am examining a system of which I am one participant, even when my own order is too small to move the price noticeably.
There is an important asymmetry between the two views. A measured return is available after the event. The relations among every participant who helped generate it are not. I can reconstruct some by studying positions, execution, incentives and similar episodes; I will never recover all possible alternatives from the realised price alone. The epistemic problem follows from my position within a history I cannot rerun, not from the failure of a particular spreadsheet. It is why a neat historical decomposition can be accurate about what occurred and incomplete about what will happen when the arrangement changes.
Remaining coherent
What does this change in my trading? I move from tallying separate positions to tracing the relationships that can make them act together. I also design a method that can function while those relationships change. The full rules belong in Episode 2. Here the point is simpler. I can define a decision before its outcome, act on what the market shows, and then investigate whether the relationships on which that method depends still deserve my confidence.
That is different from calling every loss a regime change. A market may break out and reverse many times without invalidating a trend strategy. A run of losing trades can be ordinary variation. It can also reveal a defect in data, execution, capacity or the original research. The record has to distinguish those possibilities as far as it can. Wholeness is no excuse for vagueness.
The flock helps me hold the two levels together. I can follow one bird and measure its movement. I can also study the shape that emerges from many birds responding to one another. If I insist that only the first view is real, I miss the collective organisation. If I speak only of the flock, I lose the mechanism through which the shape is made. The trader has the same obligation to move between precise components and their changing relationships.
I can see that obligation in the simplest risk report. It may list exposures by market, each small, and calculate a portfolio total. Yet a common move can make several positions answer one another through margin, capital and shared exits. A portfolio is not merely a row of isolated trades. The relation among the trades can become the largest fact about the account. That fact was present before a crisis exposed it. The crisis makes it impossible to overlook.
I still inspect every row of the report. I also ask what connects them: shared owners, financing, exposures and exit rules. Read the relationships as part of the position. The risk that looked absent from ten small rows was in the account they formed together.
The starlings will turn again, and no still image will give us their next shape. Episode 2 asks what changes when the participants can also read a forecast of that shape and act on it.
Next: Episode 2, The Future Is Not Hidden, It Is Unwritten
Sources and notes
[1] Andrea Cavagna and colleagues, Scale-free correlations in starling flocks, Proceedings of the National Academy of Sciences 107, no. 26 (2010): 11865–11870.
[2] David Bohm, Wholeness and the Implicate Order (London: Routledge, 1980), especially the chapters on implicate and explicate order.
[3] New Scientist, “Mixed fluid returns to its original state,” video, YouTube. https://www.youtube.com/watch?v=UpJ-kGII074
Richard Brennan writes on systematic trading, complex adaptive markets, and the philosophical foundations of trend following at atstradingsolutions.com. His books include The Fractals of Finance, Complex Adaptive Markets, Carved by Impossibility and The Aussie Turtles Trend Following Guide.
Want to explore why structure exists at all?
Carved by Impossibility: What Remains When Everything Else Is Eliminated
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Want the theoretical foundation for why trend following works?
The Fractals of Finance: Determinism, Adaptation and the Geometry of Markets
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