*"[A] model will be a simplification and an idealization, and consequently a falsification. It is hoped that the features retained for discussion are those of greatest importance in the present state of knowledge."*

*- A.M. Turing.*

The real trouble with this world of ours is .. it looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait.The real trouble with this world of ours is .. it looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait.

*- GK Chesterton*
Models break. Because the world changes, the factors that drove performance yesterday may not be the same as tomorrow. This is why simple models are best in a more complex uncertain world. Complexity means there are multiple factors necessary to explain change. Uncertainty is not volatility but our inability to measure some factor or to even know it exists. A world of multiple factors which change in importance is the hallmark of financial markets

So what can be done about this problem with models and complexity?

Keep it simple. This is not the same as simplistic. You just have to realize that for each extra factor there is greater potential for something to break. Data could be wrong. The relationships can change. On the other hand, if there are not enough factors, the model will to capture a key relationship. In keeping it simple, there is the realization that a model is only an approximation and that failure is real.

We also like the construct of convergence and divergence effects to at least think about how the world operates. Markets are dynamic and move between converging to some equilibrium price or moving away from some equilibrium in response to some shock.

There are market dislocations or divergences. These "shocks" are unanticipated and will have the greatest impact if they have not even been modeled or considered. An awareness of divergences is critical to understand models as falsifications or reality. Similarly, convergence suggests that dislocations in price will move back to fair value or to what may be considered equilibrium as structured or explained in a model.The world is still driven by some fundamentals relationships.

An ebb and flow of divergence and convergence can frame why models in the short-run may not work but in the long-run may be effective representations. As Herb Stein said, "If something cannot go on forever, it will stop." The divergence of today may be the convergence of tomorrow. The model often cannot explain all divergences but may still be effective as stating that prices may move back to some norm.