How Does Complexity Science Relate To Trading? by Paul Cottrell


The market is a complex organism that exhibits self–organizing behavior.  This self–organizing behavior was well articulated by Adam Smith’s invisible hand. In an economy, the individual agents of the society interact in various ways producing microeconomic activity.  This microeconomic activity allows for price discovery and equilibrium between supply and demand.  For example, a clothing retailer sells items at an acceptable price to the clothing purchaser.  This microeconomic equilibrium might not reach a macroeconomic equilibrium, but at times macroeconomic equilibrium is reached.  I suggest that macroeconomic equilibrium is a lagging equilibrium due to other factors, such as monetary policy that might not diffuse into the individual economic agent’s interactions instantaneous. In economics we call this disequilibrium as a saddle–path, whereby equilibrium is usually not reached and vacillates around equilibrium.  

Price action in the financial markets has shown asymmetric dynamics, whereby the price dynamics going up are different than price dynamics going down.  Why is price action asymmetric? Price action is asymmetric because of the behavioral effects of the trading agents.  There is a fear that takes place in depreciating asset prices leading to a stampede of sellers.

Another aspect of asymmetry is information.  In Stiglitz (2002), information is not instantaneous; therefore there are market participants that can capitalize on this information before other market participants.  In the efficient market hypothesis (EMH), information is considered symmetric and that the average trader cannot profit on new information because the current price already has that information accounted for.  EMH cannot be true because of the increasing number of market participants that can profit from news before other market participants. 

In terms of models, traders need ways to evaluate the current state of the financial market or economy.  These traders, or market participants, use models to perform an analysis if the market is fairly priced or not.  But models have assumptions and therefore can only represent a shadow of reality pertaining to financial dynamics.  Some models are more accurate than others; but due to the feedback loops of agent’s behaviors, the dynamics change in a reflexive way—leading to possible model failure.

Models have certain assumptions on price action and these assumptions can lead to malignant states within the financial markets, whereby the herd effect of traders using a certain model paradigm can cause system failure, i.e. financial crash. When these models are used incorrectly—either by mistake or on purpose—contagion can arise.  The following are examples of when models misbehave.

  • Lehman Crash
  • Flash Crash
  • Accounting drawdowns in a portfolio
  • Mass Unemployment
  • Inflation volatility—measured  in CPI