In such an environment, it is impossible to separate individual systems from the whole, as the whole is one huge interdependent mass.

For example, financial markets, themselves complex systems, are inextricably linked to myriad other complex systems. These include, but are not limited to, human emotion, domestic economies, large global economies, local politics, global geopolitics, demographics, and even the weather.  

Needless to say, human minds cannot comprehend the result of so many variables which are constantly changing. And, computer models are difficult to create because even pinpointing which variables matter is a massive headache considering that a variable that matters today might not matter tomorrow.

The natural, and most common response that traders have to such an overwhelming task is to engage in reductive thinking.

Reductive thinking is useful in simple systems where variables are easily identifiable and change in predictable ways. This is because the systems can be reduced to smaller, simpler variables which are easier to understand, manipulated or changed in some way, then put back together again. 

However, because markets are anything but simple, reductive thinking tends to take the form of market mantras like “buy low, sell high”, “buy when everyone is fearful”, “sell when everyone is bullish”, etc.

Unfortunately, these mantras, while pithy soundbites, don’t provide much in the way of useful advice.

How low is low, and how high is high? How do you tell when everyone is fearful? How do you tell when everyone is bullish?

To be continued…