Financial Wisdom Isn’t Cyclical: How to Make Better Portfolio Decisions


Financial “wisdom” is said to be cyclical rather than cumulative, but that’s unfair. At least in the dominion of portfolio management and design, academics and money managers have made great strides in decoding Mr. Market’s cryptic signals over the past half-century. The challenge, having led the proverbial horse to water, is making him drink.

The stakes are high. History, in fact, suggests that missed opportunity costs are immense, notes “The Missing Billionaires: A Guide to Better Financial Decisions”, a new book by Victor Haghani and James White, who run Elm Wealth, a wealth management firm. Using the 19th-century industrialist Cornelius Vanderbilt as an example, the authors report: When Vanderbilt died in 1877, he was the wealthiest man in the world, and his son, Billy, inherited 95% of his father’s assets. “Within 70 years of the Commodore’s death, the family wealth was largely dissipated. Today, not one Vanderbilt descendant can trace his or her wealth to the vast fortune Cornelius bequeathed.”

What happened? The short answer: is poor wealth management. More precisely, poor design and management of the investment portfolio, are exacerbated by equally poor judgment in overseeing the deaccumulation (spending) decisions.

Financial advisory has improved since the Gilded Age created vast fortunes, but short-sighted decisions in wealth management are a hardy perennial. Haghani and White cite data published by Forbes that estimates in 2022 “there were just over 700 billionaires in the United States, and you’ll struggle to find a single one who traces his or her wealth back to a millionaire ancestor from 1900.” In fact, “Fewer than 10% of today’s US billionaires are descended from members of the first Forbes 400 Rich List published in 1982. Even the least wealth family on that 1982 list, with ‘just’ $100 million, should have spawned four billionaire families today.”

Even after accounting for dedicated efforts to give away wealth, the absent billionaires is surprising. “Our point is that, collectively, we all face a really big and pervasive problem when it comes to making good financial decisions.”

The pitfalls that led to the so-called missing billionaires include some obvious mistakes, such as being too aggressive with risk-taking and spending too much too fast. Arguably the most important decision, and one that’s a core focus of the book, is what’s known as the sizing decision – the optimal share of wealth to deploy to risk assets, or the equivalent for determining how much to spend at intervals through time. Estimating this share is “the most critical part of investing,” the authors write.

The good news is that research on the sizing decision has a long pedigree, starting in the modern era, Haghani tells The Capital Spectator in a recent interview. It starts with John von Neumann’s game theory research in the 1940s. The basic goal, he explains: “Maximize expected wealth on a risk-adjusted basis – putting a cap on maximum level of risk.”

A quantitative solution for investment sizing decisions was outlined in 1956 by John Kelly (the Kelly criterion) and later, from a somewhat different perspective, by Robert Merton in 1969 via what’s known as the Merton share. A fair amount of “The Missing Billionaires” analyzes the implications of the latter, and rightly so, since it’s a cornerstone of informed portfolio design and management. In fact, the book’s deft review and deconstruction of the Merton share methodology elevates “The Missing Billionaires” to the must-read short list of books of recent vintage within the investment genre.

At a basic level, the Merton share formula is as elegant as it is simple:

Merton Share Formula

Merton Share Formula

As an example, “The Missing Billionaires” uses the Merton share to reverse engineer the required inputs to justify a 60%/40% portfolio of stocks/bonds, a popular asset allocation benchmark. The solution points to a rough estimate of a “typical” risk aversion of 2 with a 20% annual standard deviation and an estimated 5% excess return for equities. Although some market pundits have complained that the 60/40 benchmark is subjective and therefore suspect, the Merton share analysis suggests otherwise, Haghani and White explain:

“Perhaps the 60/40 recommended stock/bond allocation isn’t quite as arbitrary as it may seem, considering that since 1900, the realized return of US stocks in excess of US government bonds was roughly 6% per annum.”

A more practical application of the Merton share factors in time horizon and the crucial calculation of estimating expected return. The key insight is that dynamic asset allocation is warranted to reflect the evolving outlook for risk and return. That leads Haghani and White to review what they see as a foundation for managing asset allocation through time: calculating the ex-ante return for the stock market – the numerator in the Merton share formula — via earnings yield, based on Professor Robert Shiller’s cyclically adjusted price-to-earnings ratio (CAPE), and inflation-adjusted bond yields (proxied by inflation-indexed Treasuries (TIPS)).

The ebb and flow of the expected performance for equities creates the foundation for a dynamic asset allocation strategy that’s informed by the changing state of market valuations. The end result: raise (lower) equity weight when the expected return is relatively high (low).

Compared with a static 65% stocks/35% TIPS portfolio since the end of 1997 (the earliest date for TIPS), the results favor the dynamic strategy. Extending the backtest to 1900 (by creating a proxy for TIPS prior to 1997) generates similarly encouraging results for adjusting equities exposure based on the fluctuating outlook for stock market performance. Better yet: the dynamic strategy outperforms on a risk-adjusted basis too, according to the historical Sharpe ratio.

“Even more remarkable,” the authors report, the dynamic strategy “outperformed being 100% in US equities, which produced a lower total return with 40% more risk.”

The authors are careful to explain that the earnings yield-based strategy, by way of the Merton share, is an analytical tool, and one that offers no guarantee of market-beating results at all times for all time periods. This is finance, after all, not physics. They also advise that the basic setup can be customized and tweaked in several ways – adding a momentum component, for instance. But as a foundational concept, “The Missing Billionaires” provides a compelling blueprint for building a dynamic asset allocation strategy and investors are well-served in reviewing the details.

The main takeaway should be familiar to well-read students of finance, namely: factoring in risk is essential for design portfolio strategy. On this point, there is no debate, providing what may be the only area of consensus in the investment realm.

The drawback, if you can call it that, is the extra work required to manage a dynamic asset allocation strategy vs. simply adopting static weights and periodically rebalancing. Minds will differ on which approach is more practical. In defense of the dynamic model, Haghani and White summarize the key advantage of crunching the numbers:

“No doubt, implementing a dynamic strategy is more complex and takes more attention than following a static-weight policy. On the other hand, a rules-based dynamic approach may be easier for an investor to stick with because it can satisfy the investor’s desire to feel responsive in the face of a changing world.”

Simply put, the opportunity to combine an element of behavioral risk management with a solid quantitative methodology for asset allocation is a tough act to beat in the pursuit of keeping would-be billionaires of the future in the winner’s circle.

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