Stock Investment - Inflation, Predictions, Disruptions

Important and Unknowable

Economic predictions have always been highly variable and uncertain, and, for some reason, relied upon as if the future were a magical algorithm. Essentially, economists would make one fundamental mistake. They thought they were practicing a science. Data could be collected, inputted, and a predictive algorithm could be generated. Even Nobel Prize winners like Paul Samuelson believed that with enough data we could come to understand the economy and how it functioned.

This is nonsense. As Daniel Kahneman and Amos Tversky have shown us, human behavior and irrationality, combined with unpredictability and randomness (thank you Naseem Taleb) make this even a questionable social science. Using existing analysis and algorithms to reliably forecast is a fool’s errand, essential for someone’s tenure, and maybe even a Nobel Prize, but doesn’t add much that is useful. Some of the more laughable Nobel Prizes have been given to people who determined that markets were efficient. They are not. Economies can be predicted with useful data input. They cannot. A couple of inputs about inflation and the unemployment rate, and we know how to manage an economy. We can’t. That last one is the Philip’s Curve – true for a limited time and then it goes spectacularly wrong – a lot like most risk and market prediction models.

Beware of Experts

Look at the facts not the opinion about the facts. Anyone holding themselves out as an expert has, a very deep but narrow knowledge base that is rarely universally applicable. Fundamentally, listening to opinions rarely give useful insight. Often, it assumes looking backward but does not apply to the current situation. Global commerce, trade (and trade wars) tariffs, flexible manufacturing, and global markets, along with technological innovation and automation create significant pressures against inflation, regardless of employment levels. These are the set of facts to be considered, not an assumed economic model where few people understand the actual inputs from 50 years ago.Another example looks at revenue projections based on historical business models. But what happens when those business models are changing? We discussed the example of the metamorphosis from Blockbuster to Netflix where a fundamental change in the business model made revenue projections from the historical model meaningless. Then, Netflix had to change their business model again to one of the original production and international expansion – once again obviating existing models for revenue. Facts are what happened. Specific and verifiable. Knowledge is the appropriate combination of facts. Knowledge comes from understanding the facts that matter. Wisdom is the insight that leads to prediction. At its core, any investment strategy predicts the future. To predict the future effectively one needs the wisdom to grasp what will happen. Of course, this cannot be known, and there are many random events that can affect the future (see Anti-fragile and Fooled by Randomness by Naseem Taleb), and uncertainty should always be factored into any investment decisions or predictions.

First Principles – Disruption’s Source

“Assume no knowledge” (Socrates) No successful company can create or sustain its competitive strength without constantly examining its First Principles. It means defining a problem effectively, understanding the actions needed, and then implementing those plans. This requires a unique combination of perspective, talent, drive, and organizational flexibility. It is rare, but when discovered, it is