As an old saying goes, a man with a watch knows the time, but a man with two watches can never be sure. By having multiple models, have we simply muddied the waters?
If your goal in expectations modeling is to determine the exact return of an asset in the future, multiple models may, or may not be, useful. Trying to estimate an exact figure, however, is almost impossible to consistently achieve. None of the models discussed in this article would be a particularly effective approach for achieving this objective.
If your objective, as ours, is to use expectations as a mechanism for reducing the odds of a portfolio missing the level of return necessary to meet predefined spending needs, such as the 5% challenge in West and Masturzo (2016), multiple models can be extremely helpful. The use of multiple models allows investors to create portfolios based on different perspectives, similar to blending factor portfolios to gain particular exposures—the recent rage in equity investing.
Using each model, we can create a strategic asset allocation portfolio (called the “efficient portfolio” on the AAI platform) for varying levels of risk. Portfolios based on the yield-plus-growth model have an income focus, while those incorporating valuations adopt a mean-reversion perspective. Blending portfolio allocations based on different expectations models has the added benefit of reducing model risk inherent in any individual model, even these two models, which have some definitional overlap.
With those two extremes an investor is able to blend portfolios based on personal constraints (such as tracking error or investment beliefs about, for example, the richness or cheapness of assets) in order to construct a portfolio with the multiple perspectives that address their specific needs. This approach acknowledges that no single strategy is appropriate for all investors all the time by providing an extensible framework to meet the diverse needs of investors.