Chaos Theory and Investing – Is the Future Predictable?
Can investment performance be predicted? Charlie Bobrinskoy examines two fundamentally different investment philosophies: Determinism and Chaos Theory.
There are two fundamentally different philosophies about how to secure excellent investment results. No, not growth versus value – not active versus passive- not even stocks versus bonds. The two different approaches to investing come from a core conflict in the history of physics: Determinism versus Chaos.
Quant investors, algorithmic traders and long-term economic forecasters; all, whether they know it or not, are heavily influenced by Determinism. As we will see, Determinism teaches that the more information you have, the more research you do, the more sophisticated and complex your model is, the better your predictions will be. This theory is popular in academia and with new business-school graduates. Many leading merger and acquisition firms like Goldman Sachs use complex, long-term financial models as the basis for their recommendations on multibillion dollar acquisitions.
In the other camp are the Chaos Theorists who believe financial forecasts decline in accuracy over time. They suggest investors should focus on how businesses are run and ignore stock market gyrations. Warren Buffett is famous for this approach. Why is there this dichotomy and what does the history of physics tell us about who is right?
These two theories are rooted in physics. Determinism is a belief that everything in the world is matter, and everything that happens in the world occurs because matter interacts with other matter in a predetermined and completely predictable way. This idea dates back to Newton’s laws of motion – the amount of force it takes to produce a certain amount of acceleration is always F=MA. It is a LAW, not a guideline or a rule of thumb. It predicts exactly what will happen when two objects meet. Nothing is left to chance. If one had perfect knowledge about the location and motion of every particle in the universe, one could make perfect predictions about the future. The future is determined and predictable.
Determinism shows up in investing strategies like quant investing, bank stress tests and long-range earnings forecast models in which practitioners make confident predictions about future financial results based on complex mathematical models.
Chaos Theory adherents date back to the 1960s and Edward Lorenz of the U.S. Army Corps of Engineers. He was working on models to predict weather and found that small changes could greatly affect simple systems. Tiny errors compound over time. The mismeasurement of temperature at the fifth decimal point could turn a prediction of clear skies two weeks from now into a real world thunderstorm. His research is known as the “Butterfly Effect” from his 1963 paper on the subject, “Deterministic Nonperiodic Flow” (commonly referred to as, “Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?”).
While the title of his paper is not technically true, Lorenz proved there is always measurement error, making accurate long-term predictions impossible, even in theory. This research is officially called dynamical instability, but is better known as Chaos Theory. Chaos Theory disputes that the secret to making good predictions is getting more and more data.
The development of Chaos Theory amplified consequences of another 20th century discovery in physics namely Quantum Mechanics and the Uncertainty Principle. Werner Heisenberg showed that it is impossible to simultaneously know both the exact position and momentum of an object. The more one knows about the former, the less one knows about the latter. If this is true, Determinism’s core idea, that one could at least in theory, know the future by exact knowledge of the present, is false.
The butterfly effect is not everywhere. It doesn’t apply to systems that settle in an equilibrium – say Lehman Brothers stock price, which will remain at zero – or systems that oscillate periodically, like ocean tides.
And the butterfly effect doesn’t dismiss deterministic systems entirely. The key is understanding the Horizon of Predictability: how long does it take before small errors compound to become large mistakes. For the weather, it is about seven to ten days. A prediction of rain three weeks from now is no better than a coin flip.
What is the horizon of predictability for stocks? It depends. Some company’s future earnings are more predictable than others. Johnson & Johnson and Netflix, Inc. are both great companies, but the earnings of the former are much more predictable than the latter. An estimate of J&J’s earnings two years from now might be accurate plus or minus 10% while Netflix earnings estimates might have a 40% margin of error. Current year forecasts might be reasonably accurate, and you might even be able to make prognostications for the next year, but anybody who claims to know what’s going to happen with a company’s earnings three years from now is probably fooling themselves. You will do better studying the strengths of a company’s market position and the barriers to entry from new competitors, rather than basing a decision on a discounted cash flow model with gross margin estimates in year 20.
To use Chaos Theory in your own investment research, think about it as one of several mental analytical tools, particularly when you feel confident about a prediction. Many people think they're able to see the future much better than they actually can. Chaos theory is a good counterbalance to the psychological tendency toward overconfidence.
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