Built for What We Cannot Foresee
What five centuries of managing uncertainty can teach us about surviving the next surprise
A Venetian merchant commits capital to a ship that may never return. An eighteenth-century insurer studies mortality tables before making promises that may not be settled for decades. A derivatives trader uses a formula to value an option. A modern bank finances a portfolio of highly rated securities with borrowed money.
Each is trying to make a decision before the outcome is known. The tools improve over time, but the underlying problem remains. A useful calculation can tell us something important about a risk without telling us everything we need to survive it.
That distinction runs through this series. Sharing a voyage limits the loss borne by one merchant. A mortality table reveals patterns across many lives. An option-pricing model clarifies the relationship between a claim and a changing hedge. A portfolio model estimates losses under a defined set of conditions. These are genuine advances. The danger begins when the reach of the tool is confused with the reach of the world.
Five centuries of risk management do not lead to a method that finally removes uncertainty. They lead to a more practical conclusion. Measure what can be measured, understand what the measurement leaves out, and arrange the exposure so that a surprise does not end the game.
A voyage worth surviving
The merchants of Venice did not need a theory of complex systems to understand concentration. A voyage could promise an attractive return and still ruin the person who financed it. By sharing the capital at stake, merchants could participate without placing their entire future on the fate of one ship.
Marine insurance developed the same practical idea in another form. Part of the financial consequence of a lost vessel could be transferred to an underwriter in exchange for a premium. The storm remained uncertain. The contract decided who would bear the loss if it came.
At Edward Lloyd’s coffee house, information became part of that decision. Reports about vessels, captains, routes, weather, war and piracy helped an underwriter decide what premium to charge and how much of a voyage to accept. News from a distant port did not reveal whether a particular ship would arrive safely. It could show that the price offered for its risk no longer made sense.
None of this produced perfect judgement. Merchants still overreached. Underwriters still mispriced voyages. Some accepted more risk than their capital could support. The enduring contribution was not prediction. It was the ability to divide an exposure, change its price or decline it altogether.
The same discipline matters now. Before asking how much a position might earn, the person supplying the capital has to ask what could force it to be closed and whether the remaining portfolio could continue without it.
What a model can answer
Mortality tables showed how repeated observations could turn uncertainty into a workable commercial estimate. The timing of one person’s death remained unknowable, but a large and reasonably stable group displayed regularities. Those patterns helped insurers price long-term promises with far greater discipline than intuition alone could provide.
Option-pricing theory addressed a different problem. Under specified conditions, the exposure of an option could be approached through a changing position in the underlying asset. This linked valuation to replication and hedging. It transformed derivatives markets because it gave traders a coherent way to think about risks that had previously been difficult to separate.
The conditions, however, never disappeared. The hedge had to be financed. It had to be adjusted. The underlying asset had to remain tradable. Prices could not leap so far between adjustments that the intended hedge became something quite different in practice.
This does not diminish the mathematics. It tells us what question the mathematics answers. A model may describe an exposure under stated assumptions with great precision. The person using it must still decide whether those assumptions are close enough to the market in which the position has to live.
Long-Term Capital Management brought that problem into sharp relief. Many of its trades were based on relationships that the fund expected to converge. Even if the long-run judgement was sound, the route mattered. Losses, collateral demands and pressure from lenders could exhaust the fund before the expected convergence arrived.
The financial crisis of 2008 followed a different path. Weak mortgages were placed into securities, divided into claims with different priorities and distributed through the financial system. Models and ratings helped investors assess those claims, but the securities were also connected to short-term funding, collateral agreements and institutions that could be forced to sell. Once losses and doubt began to spread, those connections carried the damage well beyond the original loans.
The recurring question is therefore larger than the estimated loss. What must remain available, liquid or trusted for the position to survive?
Risk created by the response
Article 7 examined markets as systems whose participants react to one another. This changes the analysis because the response to a disturbance can become part of the disturbance itself.
A falling price may trigger a risk limit. The resulting sale pushes the price lower. Another institution then breaches its own limit and sells into the same market. A rule that appears prudent when considered within one portfolio can add to instability when many portfolios behave alike.
Complexity science gives us ways to study these interactions. It does not predict the date or cause of the next crisis. Its value lies elsewhere. It helps reveal how leverage, funding, imitation and feedback can turn an isolated loss into a wider event.
Historical data, stress tests and risk estimates still matter. They give us evidence and force us to specify what we believe. They become more useful when paired with questions that reach beyond the position itself. Who else owns the asset? What might make them sell? How quickly could collateral requirements change? Would the hedge still be available if everyone wanted it at once?
Uncertainty does not enter only through an event no one imagined. It also enters through reactions that no isolated calculation can fully capture.
How I choose to respond
My response is a diversified systematic trend-following programme. It does not require me to identify the next crisis, choose the market in which it will appear or decide in advance which direction prices will move.
The programme begins with small initial risk across a broad range of liquid markets. Entry and exit rules determine how positions change as prices move. Most signals will not become exceptional trends. Some will reverse and produce losses. Those losses are expected and must be small enough for the programme to keep operating.
This does not mean the portfolio enters every crisis with the right positions. A shock can arrive before a signal develops. Markets can move violently and reverse before the rules can respond. A profitable position in one market can be offset by losses elsewhere. Trend following is not a standing insurance policy, and it should not be presented as one.
Its opportunity appears when a move persists. The programme does not need to know why the trend began or where it will finish. If the rules identify the movement and the position remains manageable, it can participate while the trend continues. Research across futures markets has found evidence of this behaviour over long periods, including strong results during some episodes of market stress. Outcomes still depend on the markets traded, the rules used, implementation costs and the particular path prices take.
Position sizing holds the approach together. A trader who takes too much risk on ordinary signals may not remain solvent, liquid or psychologically capable of holding the rare position that matters. Diversification creates more opportunities, but it does not guarantee that markets will behave independently when conditions become extreme. Execution, funding and adherence to the process belong in the risk calculation.
I use trend following because it lets the response develop from observable price movement rather than from confidence in a forecast. It gives me a way to act when the cause is unclear and the eventual scale of the move is unknowable. It does not remove uncertainty. It gives uncertainty somewhere to go without requiring one early judgement to be exactly right.
The lesson that remains
The history of risk management is not a contest between practical wisdom and mathematics. Insurance made ventures possible that few individuals could have financed alone. Actuarial work gave insurers a sounder basis for long-term promises. Mathematical finance transformed the pricing and hedging of contingent claims. Complexity research has made feedback and interdependence harder to ignore.
Each advance deserves to be kept. Each also has a boundary.
For a trader, those boundaries become practical questions. How much capital is at risk? What could force the position to close? What happens if several markets move together? Can the portfolio be financed through a difficult period? Will the intended exit exist when trading becomes disorderly? If an unusual trend develops, is the position large enough to matter but small enough to survive its reversals?
No single number settles those questions. Nor can risk be removed while return remains. The task is to decide which risks are worth taking, keep the foreseeable damage within tolerable limits and retain enough flexibility to respond when events depart from the plan.
That is where five centuries of effort leave us. We have better maps, richer data and more powerful tools than the Venetian merchant could have imagined. We are still committing capital before the voyage is complete.
The sea does not consult the contract. The market does not consult the model. Both can be studied, priced and prepared for, but neither can be made to obey.
The aim is not to eliminate surprise. It is to remain capable of acting after surprise arrives.
Next: Series Synopsis
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
The book explores the architecture of constraint, emergence, and reality itself, and what it means for how we understand markets, life, and the universe.
Available now on Amazon in paperback, hardcover, and Kindle.
Want the theoretical foundation for why trend following works?
The Fractals of Finance: Determinism, Adaptation and the Geometry of Markets
The book explores the full architecture of feedback, fat tails, and fractal structure in financial markets, and what it means for how we trade, invest, and understand risk.
Available now on Amazon in paperback, hardcover, and Kindle.
Want a practical field manual for trading trends and capturing outliers?
The Aussie Turtles Trend Following Guide: A Field Manual for Hunting Outliers adapts the timeless principles of the original Turtle traders into a systematic, rules-based approach for modern markets. Co-authored with Adam Havryliv.
Available now on Amazon in paperback, hardcover, and Kindle.