Complexity Economics - Implications for Investors

The vast majority of investors make trading decisions based on their belief of how the economy will behave in the future. Changes in economic conditions have a significant impact on the price of financial instruments and those who believe conditions are likely to improve will buy (go long), while those who believe that conditions will deteriorate will sell (go short). However, while so many individuals make their investment decisions based on economic predictions derived either by themselves, or others, the fact of the matter is that most of these predictions turn out to be wrong. While there are certainly times when an individual will make a correct call relating to a specific time or part of the economy, to find an individual who consistently makes correct and timely predictions is extremely difficult, if not impossible. The majority of the predictions, or maybe a better word would be guesses, and especially those voiced through the mainstream media outlets are typically based on traditional economic theory and analysis models. However, a relatively new way of viewing the economy, known as complexity economics differs strongly from the views held by traditional economists and may help reveal why predictions based on traditional theory are so often incorrect, and as such also has significant implications for investors utilizing these methods.

Traditional economic theory has long made the assumption that over time markets move towards an equilibrium level, and by determining this level one can predict the future level of economic activity. More specifically, traditional economic theory holds the view that as long as there are no exogenous shocks to the economy (i.e. things such as changes in interest rates, innovation, increases in productivity, etc...) then one can use traditional models to determine future equilibrium levels and as such hopefully make an accurate prediction. However, in order to justify the assumption that markets always move towards equilibrium traditional economists had to make another massive assumption which in essence is the cause of traditional economics lack of success at making predictions, and this assumption was that the economy is a closed-system. A closed-system can be defined as "a system having no interaction or communication with any other system - no energy, matter, or information flowing into or out of it" (Beinhocker, 2006), and a defining characteristic of closed-systems is that unlike open-systems over time they have a predictable outcome, equilibrium. While viewing the economy as a closed-system allowed economists to believe that future economic activity could be predicted with a fair degree of accuracy, the fact of the matter is that the economy is an open-system and the behavior in open-systems is so different to that of closed systems that models that are developed for closed-systems will have absolutely no predictive capabilities when used on an open-system.

An open system is a system that allows both energy and matter to flow into and out of it, and all one needs to do is to look up into the sky to realize that the economy is certainly not a closed-system as the sun provides a constant flow of energy into the economy. While the significance that the sun plays in the economy is quite obviously, it is surprisingly ignored by traditional economic theory in the classification of the economy as a closed-system. Furthermore, classifying the economy as a closed-system also contradicts the laws of thermodynamics which govern both open- and closed-systems, and given that the economy exists in the physical world these laws which are believed to be of a universal nature cannot be ignored. The laws of thermodynamics are as follows:

1. Energy can neither be created nor destroyed. It can only change forms
2. The entropy of an isolated (closed) system not in equilibrium will tend to increase over time, approaching a maximum value at equilibrium
   

The first law is fairly straightforward, and was in fact understood when traditional economic theories were first being developed. However, the second law had yet to be discovered when traditional theories were in their infant stages and is the law which traditional economic theory strongly contradicts. To further clarify the second law, entropy is basically the level or measure of disorder in a system, and in a closed-system the level of entropy is always increasing until equilibrium is reached at maximum entropy (or disorder). So for the economy to be classified as a closed-system this would mean that the amount of disorder within the economy would constantly have to be increasing with equilibrium being reached at the maximum level of disorder. But in reality this is certainly not the case as order is in fact increasing in the economy with the advancement of technologies, the building of structures, and the increased organization of people. Thus, when order is increasing (entropy decreasing) in a system (as it does in the economy), that system inherently must be an open-system as it needs new energy to flow into it (from the sun) and entropy to flow out of it (in the form of heat). For these reasons economic theory must classify the economy as an open system and not a closed one just for the convenience and simplification that doing so provides, and this is exactly what complexity economics does.

Complexity economics not only looks at the economy as being open, but also views the economy as being a specific type of open-system, a complex adaptive system (CAS). The following is how John H. Holland, one of the pioneers in the field of complex systems defines a CAS:

"A Complex Adaptive System (CAS) is a dynamic network of many agents acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents." (Holland, 1994)

While this definition can be used to describe numerous types of systems including the immune system, the brain, ecosystems, and even ant colonies, the definition also definitely applies to the economy. The economy obviously consists of a network of many agents (individuals, firms etc..) constantly acting and reacting to what other agents in the economy are doing. Also control of the economy is dispersed and decentralized as no individual or small group of individuals can control it themselves (even though certain governments may be trying to do so). And finally, the overall behavior of the economy, like that of other complex adaptive systems does indeed arise from the cooperation and competition of the individual agents, as in the economy cooperation and competition leads to innovation, growth, and an overall increase in order (decrease in entropy). Viewing the economy as a complex adaptive system differs significantly from traditional views which by characterizing the economy as a closed-system essentially led to oversimplified models which are primarily composed of linear relationships amongst variables all leading to the predictable end-state, equilibrium. However, the behaviour of complex systems is much more intricate and the following explanation by Beinhocker in his book The Origin of Wealth certainly reveals this;

"Sometimes opens systems can be in a stable, equilibrium-like state, or they can exhibit very complex and unpredictable behavior that is far from equilibrium - patterns such as exponential growth, radical collapse, or oscillations." (Beinhocker, 2006)

Due to the wide variety of behavior displayed, complex adaptive systems are extremely sensitive to initials conditions and this is another reason why the economy is so difficult to predict. What sensitivity to initial conditions means is that even if one were able to develop an accurate model for predicting the future behavior of a certain part of the economy, if the inputs into such a model (let us say for example the unemployment rate or inflation rate) are even the smallest amount inaccurate, because of the complex behavior and non-linear relationships displayed in an open-system like the economy, the results will vary significantly from the correct results had the inputs been exact. Sensitivity to initial conditions obviously posses significant problems for making economic predictions as to obtain exact values of variables such as the unemployment rate, the inflation rate or gross domestic product to name a few is nearly impossible. For example if one wanted to obtain the exact unemployment rate one would need to poll each and every member of the work force, instead of just taking a small sample as is done now and obviously undertaking a survey this massive is quite unrealistic. However, while sensitivity to initial conditions does make any hope of consistently making accurate economic predictions all that more difficult, one cannot just make massive assumptions (such as that the economy is a closed-system) and believe that by doing so they can overcome the problem posed by complex adaptive systems and actually make good predictions. Instead if future economic theory is to be more useful it must take these difficulties into account and work to obtain methods that can realistically overcome them without completely ignoring them.

This new school of economic thought is offering a lot of insight into the faults of traditional economic theory and is also casting significant doubt on the validity of consistently producing profitable investment returns based on "predicting" the economy using traditional models. Viewing the economy as a complex adaptive system makes it easier to understand why it is so difficult to accurately predict the future behavior of the economy, and why so often the economy behaves in a manner that traditional economic models cannot explain. Furthermore, complexity economics really signifies the need for serious investors to stop listening to the economic predictions made by economists, politicians, media talking-heads, and other self-anointed experts because in doing so they are in essence just relying on the lucky chance that the predictions turn out to be right. Instead investors need to explore new and innovative investing or trading strategies, including but not limited to things such as technical analysis, shorter-term fundamental analysis, and new economic analysis techniques that do not make the assumption that the economy is a closed-system. A good way to conclude is with another quote from Beinhocker's excellent book on the subject which really sums up the problem with traditional economics:

"One can thus begin to appreciate why economic forecasters have such a tough job and an even lower reputation than weather forecasters. The combination of sensitivity to initial conditions, path dependence, and immense dynamic complexity makes the economy, like the weather, unforecastable over all but the short term." (Beinhocker, 2006)