Asset Allocation Is A Strategy For Capturing Average Results

Every investment strategy has its own particular set of pros and cons. Do you know how your strategy’s profile stacks up? As a reference point, consider an unmanaged, market-weighted asset allocation strategy.

You can’t get blood out of a stone and a passive asset allocation will never confer bragging rights for dispensing the best performance (or anything close to it) relative to a broad set of strategies fishing in the same waters. What it will do is reliably deliver something approximating the average return and risk profile for the target opportunity set. That may not sound like much, except when you consider that beating the average is difficult through time.

As an illustration, consider an ETF-based formulation of the Global Markets Index (GMI.F), which holds 14 proxy funds representing a global footprint of the primary risk assets. The portfolio is unmanaged and instead lets the market’s ebb and flow adjust weights through time.

In theory, this is everyone’s benchmark, at least for a given opportunity set, which in this case is loosely defined as global stocks, bonds, securitized real estate and commodities. Theory says this reference portfolio will remain competitive most of the time and history tends to support the claim.


Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return

By James Picerno


Not surprisingly, holding GMI.F is a relatively dependable methodology to capture, at a portfolio level, the average return of the overall opportunity set. The chart below illustrates the idea by showing performances for the 14 proxy ETFs in GMI.F over the past five years (gray lines) vs. GMI.F’s wealth index (red line). For another perspective, the blue line shows an equally weighted portfolio of the 14 proxy ETFs (the equality is set at the beginning of the period and left unmanaged for the duration of the time window).

Eye-balling the results suggests that GMI.F and the equal-weighted portfolio are reasonably successful in capturing the average results. This is just one five-year period, but other time windows (longer, shorter and over different history periods) offer similar results.

Critics might ask: why settle for average when you can own the above-average assets? The problem, of course, is that predicting which assets will be top performers is devilishly difficult. That’s another way of saying that if you attempt to bet the farm on a handful of assets outperforming you could end up with below-average results, perhaps dramatically so.

By contrast, holding everything in the targeted opportunity set and weighting the assets in a reasonable way raises the probability, significantly, that you’ll earn the average result of the playing field. In fact, a portfolio that’s mindful of trading costs and engages in periodic rebalancing boosts the odds of earning moderately above-average results, especially when compared against all the active strategies fishing in the same pond.

Note, too, that a GMI.F-type strategy (or something comparable) also boosts the odds that the risk profile of the portfolio will also be average or perhaps slightly below average.

As for how to weight the assets to reliably capture the average/above-average performance results (with average or below average risk), the market-weighted asset allocation is the baseline. The equal-weighted mix is one alternative, although this approach is more sensitive to the opportunity set selected. In the example above, equal weighing tends to lag in the time period presented because the GMI.F’s particular formulation has a more granular breakdown of bonds vs. stocks, real estate and commodities. In other words, there are more bond funds in the GMI.F mix and so equal weighting gives more weight to fixed income, which has been a drag on performance relative to the higher equity weighting in GMI.F. Nonetheless, it’s telling that the equal-weighted portfolio still manages to remain relatively middling despite the structural headwinds. Keep in mind that in other asset allocation formulations equal-weighting can provide much stronger results.

The main challenge for investors who embrace alternative asset allocation strategies: how effective is your portfolio at dependably capturing (or beating) the core of beta results through time? Comparing results against a GMI.F-type benchmark, especially on an after-tax/after trading-costs basis, will likely show that Mr. Market’s asset allocation is tough to outperform.

That doesn’t mean you shouldn’t try. A market-weighted portfolio of all the major asset classes is, theoretically, the optimal portfolio for the average investor with an infinite time horizon. Since no mere mortal matches that profile, the main agenda in portfolio design and management for real people is determining how you’re different from the average investor and what that implies for your particular investing time horizon.

There are many ways to tackle this agenda. One way is to consider what the GMI.F offers on an ex ante basis and customizing that portfolio to reflect your specific investment needs and risk tolerance.


How is recession risk evolving? Monitor the outlook with a subscription to:
The US Business Cycle Risk Report


One thought on “Asset Allocation Is A Strategy For Capturing Average Results

  1. Pingback: Asset Allocation Is a Reliable Tool for Earning Average to Above-Average Returns - TradingGods.net

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.