The asset manager is an essential link in the chain between the investors principles for living and the spontaneous order of free capital markets. At Poetic Justice Capital Management, manager selection ignores traditional industry “best practices.”
Relative performance and fees are the two most popular criterion. For those who like to play analyst, capture ratios, beta, Morningstar ratings, and heat maps are added for good measure.
For us, fees are a variable we know about and can control, and very important. The others have little to do with an investor living the one life they have with confidence. They are based on the false premise that out-performance equals more dollars of future wealth. Our selection strives to do one thing – match the asset classes we model with managers that are near perfect reflections of those asset classes.
Poetic Justice Capital has created three models – the Alpha Bets, Beta Rays, and Delta Forces. As the names suggest, alpha is active, beta is risk-on, and delta is passive.
Download the tools:
- Model Results One-Year Ended: Click to Download
- Model Results Three-Year Ended: Click to Download
- Model Results Five-Year Ended: Click to Download
- Model Results Ten-Year Ended: Click to Download
Another variable we know about and can control is potential assumption errors. Hiring managers based on out-performance can only increase potential errors, while true wealth management will minimize them.
Modern Portfolio Theory already includes three potential errors – median return, standard deviation, and correlation, for each asset class. We don’t need to add more.
Yet the addition of multiple asset classes, for the sake of diversification, merely increases potential assumption errors, exponentially. What’s worse, this so-called diversification has failed during extreme markets because of two more egregious errors – unreliable data sets and subjective computer model inputs by industry prophets.
What meets the need, is easy to use, and is reliable are the essential broad market asset classes; disciplined, low-cost managers; and reliable, historical data sets.