The Portfolio Management Assumptions that Harm Clients
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Far too often, advisors accept beliefs and practices that are detrimental to the financial wellbeing of clients. By reexamining them, you can achieve better outcomes for your clients.
Let’s jump right in.
The MPT problem
Modern Portfolio Theory (MPT) is an elegantly wonderful confluence of insight and mathematics, worthy of the Nobel Prize that was awarded to its developer, Harry Markowitz. Efforts to implement MPT, unfortunately, have not been as fruitful as the theory.
The reason is simple. To build an “optimal” portfolio using MPT, you must know three things – the future expected returns, volatilities and correlations of the asset classes you use in the portfolio. The problem is no one knows what those numbers are.
This has not stopped highly paid analysts from developing surrogates for the real thing. They go by the name of “capital market assumptions.” This moniker has a reassuring ring to it, which masks what they really are: guesses about the future.
The problem, of course, is that these numbers are not fixed, but change every year, and their historical patterns and sequences are not likely to be repeated in the future. They just keep changing and rarely, if ever, line up with capital market assumptions.
You can look at historical averages, but these numbers change over time, too. In his original MPT paper, Markowitz said that history might be a good starting place, but that ultimately the “judgement of men” would be required to refine the estimates.
Whatever methodology is used, it better be spot on. Small differences in optimizer inputs can produce dramatically different outcomes. And the methodology needs to work equally well in estimating returns, volatilities and correlations across a variety of dissimilar asset classes.
Optimal portfolios are like unicorns – they don’t exist in real life. That wouldn’t be a big deal if we all could simply accept that fact and move on. Instead, we act as though our capital market assumptions had a magical predictive quality. If our models tell us to trade, we trade, thus incurring transaction and, possibly, tax costs.
The rebalancing problem
Even if our expectations about the future have not changed, we still feel compelled to tweak our portfolios to bring them back to our “optimal” mix. This process we call rebalancing. We may rebalance periodically – quarterly for example – or we may set percentage boundaries around each asset class and rebalance when they are exceeded. Either way, the underlying assumption is that our target allocation is better than the allocation the markets have given us.
Research on the value of rebalancing suggests that it has little ability to increase returns or decrease risk. Whatever utility exists depends on factors such as time period, the direction of the market and the relative future expected returns of the asset classes being rebalanced. Yet few, if any, of us take these factors into account in developing our rebalancing strategies. Instead, we employ simple, mechanical rebalancing strategies that add little or no value and may even detract from long-term performance.
The only thing we can be sure about is that our rebalancing strategies result in transaction and tax costs.