I don’t remember why I wrote this post at the time but I still think along the same lines, so let me publish this draft as well.
When it comes to benchmarking and performance, I care about two questions. 1) Am I positive for the year? 2) Am I above my benchmark? There are unlimited ways of looking at performance but in many cases these two answers tell much of the story. To compute performance, I take the change in balance from December 31st, back out the transfers and divide the result by December 31 balance. An individual who looks at much more than this is analyzing the past at the expense of the future.
Institutional metrics often permeate the non-professional circles. The places where art and science are progressed invariably become sources of leadership in a subject matter but when it comes to performance metrics, they need not be taken at face value because every tool has its purpose. Institutions have their shareholders, investors, employees, auditors, and other stakeholders who are concerned with data relevant to them. Some institutional internal methods end up on external sites as if they matter to the average person. Interestingly, over time these do become important as people bombarded with unending choices attempt to make optimal judgment calls. What is unfortunate is that many base their decisions on hypothetical mathematics.
Take this definition of Quarter-End Average Annual Total Returns: Quarter-end Average annual total return is a hypothetical rate of return on a quarterly basis that, if achieved annually, would have produced the same cumulative total return if performance had been constant over the entire period. Average annual total returns smooth out variation in performance; they are not the same as actual year-by-year results.
How about this one for Return After Taxes on Distributions: Return After Taxes on Distributions are calculated using the historical maximum federal individual marginal income tax rates associated with fund distributions and assume that an investor continued to hold the shares. Therefore, they do not reflect the federal income tax impact of gains or losses recognized when fund shares are sold. These returns do not reflect the impact of state and local taxes. Actual after-tax returns depend on your tax situation …
What is the purpose of these and many other derived data points? Why doesn’t the financial services industry attempt to simplify performance metrics? I think some of these are created to make investors feel good about their holdings. Others are created to make performance appear better in one year where another calculation method would result in inferior results. If one cannot improve performance, why not improve the way performance is computed. A third set are created because people like to overly complicate matters.
I find the same principle of too much complexity in many other departments of life. Unfortunately dealing with complexity requires energy. Therefore, we can only benefit by simplifying that which concerns us. In choosing a solution, in making a decision, in everyday life I always think “How does this help keep my life simple?” If the choice does not help simplify my life, then the next question is “Why am I willing to pay a premium (in energy) for it?”
Financial performance information should be simple and easily comparable. Performance reporting has turned into an art with mutual funds coming up with all kinds of creative ways to report performance. Attempt to compare these numbers from multiple services and you will quickly find yourself up against numerous somewhat meaningless numbers that are only good for order of magnitude comparisons (if that).