The butterfly effect is not actually real, but it is a powerful metaphor for explaining chaos theory. Tiny changes in the initial conditions can have enormous consequences in non-­linear systems. The meteorologist Edward N. Lorenz discovered this mechanism while working on a weather forecasting model back in 1961. He had fed his model with initial values that barely differed from one another—yet the results were wildly divergent. Lorenz thought it was a calculation error at first, but he then discovered the chaotic system for which he later coined the metaphor: the flap of the butterfly’s wings in Brazil that can set off a tornado in Texas.


Financial markets have a lot in common with the chaotic systems of nature. Although they are based on the laws of economics and can be predicted with complex models to a certain extent, still, even the best models involve a number of assumptions. If these change, then any prognosis will eventually go off the rails. For example, an unusual pest infestation can cause severe crop failures that ruin entire price forecasts.


Traffic jams often occur for no apparent reason—no accident, no construction site, no closures far and wide. Because heavy traffic reacts like a non-linear system, all it takes is just a few small disturbances. One driver begins to tailgate, another hits the brakes too hard—and next thing you know, a wave of stopped traffic has started to multiply.


Many animal populations undergo natural fluctuations, but they usually remain stable within them. Yet sometimes a population will explode or completely collapse. At that point, forests are suddenly full of beetles or parks overrun with hopping rabbits. These sorts of events can only be explained by chaos theory. Some fluke event and a population explodes. Take, for instance, the case of the gypsy moth: a caterpillar escaped from a laboratory in Boston and the pest overran the northeastern United States in almost no time at all.


Weather is a non-linear, chaotic system. Tiny changes in temperature, air pressure or wind direction can cause large changes in the weather thousands of kilometers away. Modern computers and sensors can simulate weather systems, but they cannot perfectly replicate them. There simply aren’t enough weather sensors for this. The further into the future the model forecasts, the greater the probability that a small variation between two sensors will lead to a deviation from the forecast.


In economic systems, even the smallest idea can quickly grow into prodigious innovations. The economists Edward G. Anderson and Nitin R. Joglekar describe these sorts of developments as innovation butterflies, in reference to the butterfly effect. As an example, Nintendo’s introduction of the Wii gaming console shook up the entire industry. Instead of better and better graphics, the new console relied on a more intuitive control concept. This resulted in a decline in sales for graphic chip manufacturers and an increase for controller chip producers.