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Asset Allocation: No One Knows The Future

Part 4

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Asset Allocation: No One Knows The Future

Alex Serman • May 24, 2024




Our fifth-and-final segment of this asset allocation saga is a radical departure from the typical approach to the topic.
We begin with this question:

“How do we develop a long-range asset allocation plan if we make no claim of forecasting skill?

Instead of creating highly-detailed estimates of the expected return and risk of every asset segment (along with the correlations between all possible pairings) we begin by simply acknowledging the typical behavior of the major asset groupings. Our focus will be on the insights we have gleaned from observing nearly a century of market returns, and drawing inferences around our understanding of the general nature of these asset classes. We will also apply more intuitive weightings to our set of complementary asset classes, with a bias toward equal weightings, both across and within asset segments.

This approach replaces assumptions about market behavior with a general understanding of the nature of these investments and their relationship to each other. This frees us from the requirement of creating detailed forecasts, along with the underlying statistics that drive the typical “mean-variance optimization” approaches. We will show that this “definitional and intuitive” approach is no less robust and efficient than the mathematically-driven approaches, which are only as good as their forecasts prove to be accurate.


We draw some critical inferences from our examination of nearly a century of returns on major investment types. This analysis produced a few insights to help us understand the behavior of these investments within market circumstances that are essentially “good” and bad.” These include:

  • Normal investment markets, where equity is rewarded with relatively high returns
  • Poor investment markets, where equity underperforms, while strong Treasury bond returns offset equity losses
  • Times of extreme global stress, where uncertainty drives a flight from financial investments, in favor of real assets.


Our approach provides at least one asset class that should perform well in every market circumstance. We acknowledge that we do not know when any of these three circumstances will occur; neither do we know how long each will last. We simply plan to hold all three asset classes, so that in every circumstance, we hold the asset class that is likely to perform best, while also owning the asset class that offers offsetting returns when the other asset classes perform poorly. For example, when equity is stressed by poor economic conditions, bonds emerge as the asset of choice in this “risk off” period. And when the market shifts to a “risk on” posture, our equity is likely to resume earning strong returns. These periods represent the typical market cycle, and our strategy demonstrates the benefits of this intuitively-diversified approach.

What about when we experience tremendous global uncertainty, when companies, economies and even currencies come under stress, as financial assets are devalued in an “absolute risk off” market posture? In this circumstance, survival replaces the normal expectation of earning a reasonable return on our investments. This is when real assets such as gold emerge as the true store of value.


We defined an equity component that benefits from normal and strong economic times. Our expectation of weak investment markets is defined by two circumstances: bad and extremely bad. The asset segments that protect our wealth during these times are also likely to grow our wealth, thereby offsetting (or at least lessening) expected losses in our equity investments. Since we cannot predict which of these weak markets may occur next, we equally weight our Treasury bonds and gold, creating a “reserves” category to guard against all “bad” markets.

Now the question is: how much should we allocate to our “growth” and to our “protection” assets?

Acknowledging that we have no insight into the future, our suggestion is to invest equally in each broad asset grouping: half in equity and half in our reserves group. This mathematically-neutral weighting produces the following allocation:

Our equity is a “70-30” mix of large stocks and small stocks, representing the US stock market. One could easily substitute a global equity strategy; we used US equity for our illustration because of its long history.

Our bond portfolio is an equal mix of 10-year and 20-year US Treasury bonds. The equal-weighting approach provides exposure to the bond market without making a forecast on interest rates or bond maturities.


We created a “portfolio for all seasons” and we tested it throughout the circumstances of the past century, which included:

  • an ever-changing economy that moved through these periods:
    • agrarian
    • manufacturing
    • advancing technology
    • service
    • information
  • two world wars, and several international conflicts
  • globalization
  • rapid economic and geopolitical change, including periods of intense inflation amidst both growth and stagnation.

Our confidence lies in having identified the types of circumstances we are likely to encounter, while holding the appropriate investments for each of these circumstances. The observed performance of our asset segments and the overall strategy supports our expectations.

This first chart illustrates the result of creating our “growth” and “reserve” groupings from the equally-weighted segments within each. The overall asset allocation is the result of equally weighting these major asset groups.


Although our goal was not to achieve “mean-variance efficiency” we found that our intuitive, circumstance-based approach was quite efficient in the traditional sense:

  • Our reserves portfolio achieved a higher return than its highest-returning asset, while its risk was almost as low as its lower-risk component, and
  • Our total portfolio return was higher than the average of its components, while its risk was nearly as low as its lower-risk component.

We demonstrate the efficiency of our intuitive, equally-weighted solution by showing the set of possible mixes of “equity plus reserves” using the end points of “all reserves” and “all equity” – in increments of 10 percent. The resulting set of options is identical to the “efficient frontier” that is typical of the mathematically-oriented, mean-variance approaches that depend on the assumption of forecasting skill. We note that the first three allocations (from 100% reserves to 80% reserves) are “dominated” by the other allocations. This degree of “curvature” is the result of substantial diversification benefit.

We also observe that our equally-weighted approach accomplishes two critical goals:

  • it prepares and enables us to hold our strategy across all market circumstances, and
  • it provides the highest possible return for its level of volatility risk.


Our intuitive approach stands up to the scrutiny of the traditional investment theory that ignores the realities of continuing to hold one’s long-term strategy in the face of increasing uncertainty. That “textbook approach” also ignores the emotional consequences of facing sustained and significant losses in some of our investments. The risk of abandoning one’s asset allocation due to human emotion and regret is never acknowledged within the traditional context, since it considers human beings to be completely logical and immune to emotional influence in their decision process.

We deliberately chose to recognize the reality of emotions and to provide a controlling safeguard: always holding something that benefits from each of the markets we expect to encounter. We are also protected ourselves from devastating loss by avoiding concentrations via an equal-weighting approach.

But how efficient is our strategy through the lens of traditional investment theory?

The Capital Market Line (“CML”) connects the risk-free asset (i.e., cash) to the so-called “efficient frontier” of diversified strategies. The tangent point identifies the true “market portfolio” from the set of possible strategies. In our case, we see that our equally-weighted strategy of equity and reserve assets is nearly perfect in its placement on the CML.

Our protections against potentially-devastating losses, fear of missing out on tremendous gains, and the risk of abandoning our asset allocation due to ill-timed, emotional trades are all part of a strategy that is equal in market efficiency to anything created using the presumption of market forecasting and portfolio optimization skill.


Our approach was definitional and intuitive. It focused on the nature of the investments we included in our strategy and their observed behavior over the past century. This included individual return characteristics plus how these behaved in combination with each other. We expressed this in common language, avoiding unnecessary jargon and complex mathematics. However, this does not imply any lack of rigor or quantitative validation of our approach.

Much of the success of our method is the result of the complementary nature of the investments. This is expressed through the correlation statistic, which is a measure of diversification potential in a pair of assets. Our strategy is somewhat unique because its components are statistically unrelated, with a zero correlation between them. This produces a significant reduction in the risk contributed by each pair of assets within the portfolio. We observe these low correlations within the reserves category, and between the reserves and the equity.

This correlation statistic is an average over time. The reality of most statistics is that they change over time, and there is insight to be gained in observing these trends over time. We also see diversification across these correlations.

A key benefit of diversification is stable portfolio returns. Another benefit is higher returns, since diversification also reduces “volatility drag” that reduces long-term return. This explains the mystery behind how the reserves group achieved a higher return than its highest-returning asset. As shown below, an investment in the blended reserves portfolio earned more than an equal investment in either of its components. Although Treasury bonds and gold earned essentially the same return over the past century, the combination of both assets earned substantially more. It also participated more in upside movements and less in declines.


By examining the trend of rolling returns, we can visualize the dynamics behind the portfolio’s diversification, as driven by the low correlation of its assets. The portfolio’s return trend is quite smooth, even though its component assets have much higher swings in their peak-to-trough performance trend lines. This validates the complementary long-term performance of the equity and reserves over the past century.

We examined the annualized returns by decade, working backward from the current date of this analysis (2023.) Despite the challenges of the past century, our intuitive strategy produced substantial returns within each decade, ranging from about 7-1/4% to about 15 percent. It is notable that during “the lost decade” of the 1970s, when US equity “went sideways” and earned essentially nothing after inflation, our portfolio produced an inflation-adjusted return of almost 6-1/4 percent.


The next phase of the investment process turns a plan into a portfolio. The decision process around portfolio construction can be quite robust – it is more than simply “picking stocks!” This phase presents tremendous opportunities to help clients meet their financial goals by enhancing returns while also managing the various aspects of risk to acceptable levels. We hope to go beyond the traditional approach by introducing innovations that touch the areas of risk management, investment selection, and performance evaluation.




Written in partnership with Stephen Campisi