The tactical is vastly more interesting than the strategic when it comes to investing, but the latter is vastly more important for determining results. Unfortunately, coming up with reliable numbers is a challenge, and even in the best of circumstances the estimates are only guesses. Ideally, they’re informed guesses, but guesses nonetheless.
No matter, as guesses are all we’ve got for strategic portfolio design. The three building blocks in the endeavor of building efficient portfolios (i.e., portfolios that maximize return for a given level of risk) are expected returns, volatility (standard deviation) and correlations for the major asset classes. The latter two tend to be relatively easy to project based on a careful sampling of history. Expected returns, however, are another animal, and this is where the challenge lies. Simply put, projecting returns far into the future is at once immensely critical for long-term portfolio design, and immensely difficult. The reason: history is of limited value in determining performance in the years ahead.
That said, we’re more than a little interested when a respected research team brings fresh numbers to the genre of strategic projections. On that score, we refer you to EnnisKnupp. The Chicago-based institutional investment consultant last month updated its Capital Markets Modeling Assumptions, with an eye on assessing the outlook for returns, correlations and volatility among the major asset classes. Strategically minded investors would do well to give the research paper a read and consider the implications for portfolio design. Granted, the paper dispenses estimates, but robust ones nonetheless. As a result, the numbers offer a starting point for deciding how to structure a portfolio. As a preview, here’s a sampling from the paper’s statistical offerings:
Asset Class Expected Long-Term Compound Return
US Equity 7.5%
Non-US Equity 7.2
US Bonds 5.6
Real Estate 6.5
Historical Asset Class Standard Deviation (1978-2005)
US Equity 16.7
Non-US Equity 18.7
US Bonds 6.6
Real Estate 11.3
Historical Asset Class Correlations (1978-2005)*
Relative to US Equity:
US Equity 1.00
Non-US Equity 0.71
US Bonds 0.20
Real Estate 0.59
Relative to Non-US Equity:
US Equity 0.71
Non-US Equity 1.00
US Bonds 0.20
Real Estate 0.63
Relative to US Bonds:
US Equity 0.20
Non-US Equity 0.20
US Bonds 1.00
Real Estate 0.58
* 1.0 is perfect positive correlation; 0.0 is no correlation
We’re fairly confident that the standard deviations and the correlations will prove reliable, if not perfect benchmarks for the future for the simple reason that history is a fairly good guide for such measures. Expected returns, of course, are another matter, requiring more than a little suspicion as to their accuracy relative to what the future brings.
That said, one thing stands out in the numbers: the low correlation of bonds relative to equities. In fact, that’s consistent with history. The no-brainer diversification decision has long been one of adding bonds to a stock portfolio. If nothing else, the EnnisKnupp numbers reaffirm that the strategic does in fact trump the tactical as a vital issue for investing success. We can debate what the Fed will do next, and whether inflation is rising, falling or standing still. Exciting as all this is, it pales in importance next the recognition that bonds are likely to remain excellent diversification tools for equities. This, at least, is one paradigm that looks set in stone.