How Beliefs Become Structure and Structure Becomes Belief
“We do not see things as they are, we see them as we are.” - Anaïs Nin
In 1992, George Soros broke the Bank of England. He bet ten billion dollars that the British pound would be forced out of the European Exchange Rate Mechanism, and he was right. The pound collapsed. Soros made a billion dollars in a single day. It was one of the most celebrated trades in financial history.
The standard telling frames this as a triumph of analysis. Soros saw that the pound was overvalued, that the Bank of England could not sustain its exchange rate peg, that the macroeconomic fundamentals pointed to devaluation. He saw the truth, and the truth made him rich.
But there is a deeper story, and Soros himself would be the first to tell it. His bet was not merely a response to the fundamentals. His bet changed the fundamentals. Ten billion dollars of selling pressure on the pound accelerated the very devaluation he had predicted. His analysis was not wrong, but it was also not purely observational. His observation was an intervention, his prediction a force. He did not merely see the future; he helped build it.
This is reflexivity. And while Soros named the phenomenon and profited from it spectacularly, the dynamic he identified runs far deeper than any single trade. It is the engine through which beliefs become structure and structure becomes belief, an endless recursive loop that is not a distortion of markets but the way markets construct themselves.
Beyond Soros: Reflexivity as Construction
Soros described reflexivity as a two-way feedback between market participants’ perceptions and the situations they are trying to perceive. Participants form views about the market. Those views influence their actions. Those actions change the market. The changed market feeds back into the participants’ views. And so the loop continues.
It is accurate enough as far as it goes, but it frames the problem as one of distortion. In the Soros framework, there is a reality out there, and reflexivity causes prices to deviate from it. The implication is that reflexivity is a temporary aberration, a bias that eventually corrects as reality reasserts itself.
In a complex adaptive system, the picture is more radical. Reflexivity is the mechanism through which reality gets constructed in the first place. The beliefs of participants do not merely influence prices. They harden into structural elements of the system itself. They shape capital flows, risk tolerances, liquidity provision, and institutional behaviour in ways that persist long after the original beliefs have been forgotten. The loop does not distort the fundamentals. The loop builds the fundamentals.
This is the difference between reflexivity as Soros described it and reflexivity as a property of complex adaptive systems. In Soros’s version, beliefs and reality are separate things that influence each other. In the complex adaptive version, the boundary between belief and reality dissolves. Beliefs serve as building materials. What participants think about the market becomes part of what the market is.
Risk Models as Risk Factors
Consider the most consequential example of this dynamic in modern finance: the role of Value at Risk.
VaR was designed as a tool for measuring risk. Banks used it to calculate the maximum loss they could expect over a given time horizon at a given confidence level. Regulators adopted it as the basis for capital requirements. Risk committees used it to set position limits. It was, by every conventional standard, a tool for observing and managing an external reality: the risk embedded in a portfolio.
But VaR did not merely measure risk. It structured risk. When volatility declined, VaR models indicated that risk had fallen. Lower risk reduced capital requirements, and institutions responded by taking on more leverage. The larger positions, funded by abundant credit in benign markets, suppressed volatility further, which pushed VaR lower still and licensed another round of leverage.
The measurement was feeding the system it was measuring. The observation was creating the conditions it was observing. And when the cycle reversed, when volatility spiked and VaR surged, the same dynamic ran in the opposite direction. Higher VaR meant higher capital requirements. Higher capital requirements meant forced deleveraging. Forced deleveraging meant selling. Selling meant more volatility. More volatility meant higher VaR.
The risk model had become a risk factor. The tool designed to measure the system had turned into a structural component of it, amplifying the very dynamics it was supposed to quantify. The model had not failed. Its mathematics were sound. What happened followed from embedding it inside the system it was built to describe. The measurement became part of the measured. The map became part of the territory. And the territory shifted accordingly.
The Recursive Engine
The VaR example is dramatic, but the same dynamic operates everywhere in markets, at every scale, in every timeframe.
Consensus forecasts shape earnings expectations. Those expectations move stock prices, which create wealth effects that spill into consumer spending and feed back into the economic data that shapes the next round of forecasts. Round after round, each stage feeds the next, and the “fundamentals” at any given point are partly a product of the beliefs that preceded them.
Narrative frameworks operate the same way. When the dominant narrative says that technology stocks are the future, capital flows into technology stocks. The inflows drive prices higher. Higher prices generate returns that confirm the narrative. The confirmed narrative attracts more capital. At no point in this loop is the narrative “wrong” in any simple sense. The narrative is producing the evidence that supports it. It does not describe an external reality so much as construct one.
Credit markets provide perhaps the most vivid illustration. When a company is perceived as creditworthy, it can borrow cheaply. Cheap borrowing improves its financial ratios. Improved ratios confirm its creditworthiness. The perception funds the reality that validates the perception. Reverse the cycle: when creditworthiness is questioned, borrowing costs rise, financial ratios deteriorate, and the original concern becomes self-confirming. The company’s actual financial health is not independent of the market’s belief about its financial health. The two are coupled, structurally and inescapably.
Beliefs as Building Materials
The traditional view of markets assumes a separation between the observer and the observed. There is an economy, a set of fundamentals, a reality. Participants form beliefs about this reality. Those beliefs may be right or wrong, but they are about something that exists independently of the believing.
Reflexivity collapses this separation. In a reflexive system, beliefs are not merely about the world. They are in the world. They are structural elements, as real as capital, as tangible as order flow, as consequential as any balance sheet entry. When enough participants believe a trend will continue, their belief creates the buying pressure that continues the trend. When enough participants believe a bank is sound, their belief ensures the deposits that keep it solvent. When enough participants believe a currency is stable, their belief generates the capital flows that stabilise it.
None of this is crowd psychology in the simplistic sense, emotion overwhelming reason, or irrationality defeating rationality. The participants in these loops may be perfectly rational, acting logically on the information available to them. Reflexivity asks only one thing: that actions based on beliefs change the conditions that determine whether those beliefs are accurate. And in a system where participants act on their beliefs, and where actions aggregate to produce the conditions participants observe, this requirement is always met.
The embedded agent, therefore, is not merely inside a system that responds to beliefs. The embedded agent is inside a system that is built from beliefs. Your beliefs about the market, and everyone else’s beliefs about the market, and everyone’s beliefs about everyone else’s beliefs, are raw materials in an ongoing construction project whose output is the market itself.
The Ouroboros
There is an ancient symbol that captures this dynamic with unsettling precision: the Ouroboros, the serpent eating its own tail. The creature sustains itself by consuming itself. The end feeds the beginning. The process has no external input and no external reference point. It is entirely self-contained, entirely self-referential, and entirely real.
Markets are Ouroboric. They feed on themselves. Prices generate the data that generate the models that generate the positions that generate the prices. A narrative draws in capital; the capital produces returns; the returns become the evidence that keeps the narrative alive. Risk models impose constraints, the constraints shape behaviour, and the behaviour throws off the very volatility the models were built to measure.
Circular reasoning is a logical fallacy. What markets perform is something else entirely: circular construction. The loop isn’t making an argument. It is laying bricks. Each pass through the cycle adds structure, adds capital, adds positioning, adds complexity. The market at the end of the loop is not the same market that entered it. Something has been constructed. And the construction is real, even though the process that built it was self-referential.
This is why reflexive bubbles are not illusions. A bubble built by reflexive feedback is a real thing. The prices are real. The capital flows are real. The wealth effects are real. The economic consequences are real. The fact that the structure is self-referential does not make it imaginary. It makes it fragile. Because a structure that is built from beliefs can be dismantled by the withdrawal of beliefs, and the dismantling is as real and as consequential as the construction.
Navigating the Loop
How does the embedded agent operate inside a reflexive system?
The first step is to stop looking for the “true” fundamentals behind the reflexive feedback. In a fully reflexive system, there are no fundamentals independent of the beliefs about them. This does not mean that analysis is pointless. It means that the object of analysis changes. You are not trying to see through the reflexivity to some hidden reality beneath. You are trying to understand the reflexive process itself: its direction, its intensity, its fragility, and its structural dependencies.
A trend follower is, in this light, a reflexivity surfer. The trend follower does not ask whether the trend is “justified” by fundamentals. The trend follower recognises that in a reflexive system, the trend is partly constructing the fundamentals that would justify it. The trend is real. The feedback is real. And riding the feedback, with appropriate risk management, is a legitimate strategy precisely because reflexivity is a structural property of the system, not an anomaly to be corrected.
But the trend follower must also understand the fragility of reflexive structures. The same feedback that builds the trend can reverse and destroy it with equal speed. When beliefs shift, the cycle reverses. The construction unwinds. The capital that flowed in now flows out. The evidence that supported the narrative now contradicts it. And the reversal, like the construction, feeds on itself.
The embedded agent’s protection against reflexive reversal is not prediction. You cannot predict when beliefs will shift. The protection is structural: sizing that survives the reversal, diversification that ensures no single reflexive loop can be lethal, and the discipline to remain engaged across the full cycle of construction and destruction.
The Building That Reshapes the Wind
In architecture there is a phenomenon called the Venturi effect: wind funnelled between tall buildings accelerates as the gap constricts it. The buildings shape the wind. But the wind also shapes the buildings, weathering facades and eroding materials, teaching each generation of architects to design for the patterns the last generation created. Built environment and wind are coupled, each reshaping the other.
Markets are this kind of system. Your models, your positions, your beliefs are the buildings. The market’s dynamics are the wind. You build structures (strategies, portfolios, risk models) based on your observation of the wind. But your structures change the wind. And the changed wind reshapes what you build next.
There is no equilibrium here, no point at which buildings and wind settle into a stable configuration. Each adjustment throws off new patterns and new eddies. The system stays in motion, permanently under construction.
The embedded agent does not seek equilibrium. The embedded agent builds for turbulence. Knowing that your structure will change the wind, and the changed wind will test your structure, you build with flexibility and deep margins of safety, expecting that the very conditions you designed for will be altered by your design. This is the practice of embedded reflexivity: constructing and adjusting, endlessly, inside a system that is constructed and adjusted by your construction and adjustment.
Your beliefs are building materials. What the market becomes tomorrow is partly a function of what you believe about it today. And what you believe tomorrow will be a response to the market your beliefs helped to build.
The loop does not end. The serpent does not release its tail. You are inside the Ouroboros, and the only option is to build well within it.
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 and Complex Adaptive Markets. The forthcoming Carved by Impossibility completes the trilogy.
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