In the hierarchy of investment decisions, asset allocation is at or near the top of the list of variables that are strategically relevant for diversified portfolios. There are a number of studies telling us so, starting with the influential Brinson study from 1986—“Determinants of Portfolio Performance”—and its 1991 update. The basic message: asset allocation matters.

Deciding how much it matters, why it matters, and under what conditions has spawned a fierce debate over the years, along with a small library of research analyzing the details. A paper a few years back from Ibbotson Associates (now a part of Morningstar) captured the spirit of the discussion with this title: “Does Asset Allocation Policy Explain 40, 90 or 100 Percent of Performance?” The answer? All three accurately summarize asset allocation’s influence, but it very much depends on how you define the question.
As the Ibbotson paper explains, “asset allocation explains about 90 percent of the variability of a fund’s return over time but it explains only about 40 percent of the variation of returns among funds. Furthermore, on average across funds, asset allocation policy explains a little more than 100 percent of the level of returns.”
Although the Ibbotson research helps clarify the dispute over how and why asset matters, it’s hardly the last word on the subject. Indeed, navigating the nuances of asset allocation research, and drawing practical conclusions, has is almost a full-time job in the 21st century. Clearly, this has become a broad and deep discipline in its own right, with the no shortage of reference material to consider. Skeptical? Type in “asset allocation” at Social Science Research Network’s home page and behold the result.
Asset allocation as a formal topic of inquiry has come a long way since the 1986 Brinson study launched the discipline, and it’s still evolving. Rapidly, in many directions. There are no easy answers, but at least we know where to start. Among the standard works that deserve a spot on every strategic-minded investor’s bookshelf:
Asset Allocation: Balancing Financial Risk
The Art of Asset Allocation: Principles and Investment Strategies for Any Market, Second Edition
The Four Pillars of Investing: Lessons for Building a Winning Portfolio
All About Asset Allocation
As valuable as these books are, they only scratch the surface. Indeed, a number of niches in asset allocation are worth exploring, such as tactical interpretations. Mebane Faber’s The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets is a recent contribution to this niche. And yours truly reviews some of academic literature in Dynamic Asset Allocation: Modern Portfolio Theory Updated for the Smart Investor.
Meanwhile, the discussion over GDP vs. market-cap weighting systems is another aspect of the debate over what constitutes an effective passive definition of structuring a portfolio. A new research briefing from MSCIBarra revisits the subject by considering the differences in weighting an international equity portfolio by the size of each country’s economy vs. the market capitalization of its stock market. This is a familiar topic for MSCI, which has long published a series of equity indices weighted by GDP. How have the two methodologies fared? The GDP methodology has recently posted a considerable edge over its market-cap equivalent on a broad basis that targets all the world’s stock markets, including the U.S. For the five years through February 19, 2009, the MSCI ACWI GDP Weighted Index earned a 2.8% annualized total return–comfortably above the slight 0.3% annualized rise for the conventional MSCI ACWI, which is market-cap weighted.
It’s tempting to declare GDP weighting as the winner, now and forever more. But investors should be wary of assuming the past will repeat. It may, but we need something more than blind extrapolation of the past as a compelling argument. Indeed, one of the reasons for the GDP weighting’s edge is that the strategy holds larger portions of emerging market stocks, which grab a bigger slice of assets in GDP-oriented indices vs. market-cap benchmarks. As such, one’s views on emerging markets are critical to assessing GDP weighting.
Notably, China’s large and growing economy is under represented in a market-cap index because its stock market is relatively small compared with its GDP footprint. At the opposite end of the extreme, the U.S. market is over represented via market cap because American stocks are highly valued relative to the economy. As our chart below shows, China’s stock market capitalization represents less than 10% of its GDP value. By that standard, the U.S. is over represented because its stock market capitalization trades at a premium to the dollar value of the economy.

Presumably, such gaps will close in the years ahead. If so, the trend implies a bullish tailwind for China equities and a headwind for U.S. stocks.
But GDP is but one alternative weighting scheme, as a recent article by Rob Arnott and two co-authors reminds. It’s not always clear that an investor should assume that any one methodology will be superior in the years and decades ahead. “Our research shows that a combination of cap weight, economic scale and minimum variance creates a compelling risk/return profile,” Arnott and company write.
But there are several issues to consider. One is that passive indexes based on something other than market cap may incur higher management costs vs. a standard market cap indexing strategy. There are other details to review as well if we’re to understand why expected risk premiums might be higher for one weighting system vs. another. Overall, one can persuasively argue that higher expected returns come only by assuming different risks relative to the market cap portfolio, which is arguably the true passive definition for equities. Becoming comfortable with those risks in terms of their economic interpretation is essential before diving into alternative indexing systems.
It’s no surprise to learn that different portfolio construction techniques provide different return expectations. But these expectations, after adjusting for risk, may not be so surprising (or enticing) after all. Indeed, modern finance has identified an array of betas to consider, such as small-cap value. Is this a free lunch? No, absolutely not. Does small-cap value offer a higher expected return vs. the standard equity beta? Yes, or so it seems. But understanding why it offers a higher expected return is critical before overweighting the beta. No less is true for GDP weighting, or any other strategy that claims to capture a higher risk premium.
There are no short cuts to minting risk premiums in the money game, but there are lots of betas to consider. Choose wisely, but do your homework first.


  1. Vish Sarma

    I believe the chart above uses the GDP calculated based on purchasing power parity as opposed to nominal GDP in US$. If you consider nominal GDP for India and China both of them will be fairly close to the total stock market capitalization in US$

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