“Objectivity is gained by making assumptions explicit so that they may be examined and challenged.” – Richard Heuer, Psychology of Intelligence Analysis
Alpha Theory asks investors for a few basic inputs (used to calculate an expected return):
• How much can I make if I’m right?
• How much could I lose if I’m wrong?
• What are the probabilities of each?
When I tell folks that they MUST have these forecasts to make investment decisions, I often get a response of “sure, I can come up with them, but I have no idea if they are going to be right.” They’re basically conceding that since they’re not sure if they’re going to be accurate, then they’re not going to do it. The problem with that logic is that firms are using something to pick stocks. Position sizes don’t come out of thin air. When pressed to describe how a decision is made, these firms will describe a process that sounds very familiar to the expected return calculation. They “generally” come up with a price target. They discuss and debate downside risk. They talk about conviction level. My belief is that managers feel better about discussing the inputs in the abstract or implied sense, rather than making them explicit because they can’t be sure how “right” their explicit assumptions will be. If they do make the inputs explicit, they would rather have them all componentized on a sheet, instead of combined into a single expected return. I believe this is because of the misconception that one bad input spoils the whole calculation.
Granted, a bad input reduces the efficacy of the result, but doesn’t nullify it. But this train of thought still misses the point. The real issue is that the same good or bad inputs are going into the managers own “mental” calculation of expected return and position size. The “garbage in-garbage out” dilemma dominates whether the process is explicit or in the manager’s head. Only by making the calculation explicit do you avoid the cognitive errors of mental calculation (see the quote at the beginning of this article). Intuition and instinct and experience aren’t mitigated by making inputs explicit, they’re just externalized so they can be properly weighed and judged.
Try an experiment. Talk through a portfolio position, going through every aspect you find relevant and ask the manager, “what is the expected return and what is the right position size?” Now do the same thing and determine an explicit reward price, risk price, and the probability of each. Use those to calculate an expected return and position size. See which process is more accurate, more repeatable, and more easily monitored. I believe you’ll find that the explicit process gives you greater confidence, better communication, and improved returns with less risk.
I’ve been “spreading the gospel” about using expected return in portfolio management for eight years and have had over 2,000 meetings. I’ve noticed a change in investor mentality over that time and the biggest shift is the attitude towards process. In the beginning, I had to convince managers that they needed an explicit process to be successful. Now, my anecdotal estimate is that half of the managers I meet with already realize they need to create a more explicit process. The “chasm” has been crossed and the advantages gained from using an explicit process to pick and size stocks is moving from a competitive advantage to a cost of doing business. If a fund is still relying on instinct and heuristics to manage the fund in a few years they are going to get left behind by those that embrace process. As an analog to the shift towards process, look at the adoption of Moneyball in all sports over the 90s and 00s. Moneyball went from a competitive advantage to a cost of doing business in a matter of a decade. But unlike sports franchises which can weather long droughts of poor performance, a fund that doesn’t lead will cease to exist. Good research and stock selection will always be paramount to success. But great process is the only way to make sure great research turns into great results.