The Benefits Of Low Correlation: Round II

October 21, 2008


The CW portfolio generated a 9.64 percent IRR, but had a low standard deviation of return of 5.92 percent. Its worst one-year loss was -7.3 percent, it had annual losses 16 percent of the time and the average annual loss was a mere -2.6 percent. Only the two-asset portfolio of cash and bonds had a lower average annual loss, but the two-asset portfolio only had a 7.71 percent IRR and experienced losses 24 percent of the time.

Finally, the performance metrics for a conservative two-asset 40/60 portfolio and a moderate two-asset 60/40 portfolio are reported. Both generate impressive returns, but with higher aggregate correlation. Worst-case one-year losses were higher than in either seven-asset portfolio, as was the frequency of loss and the average annual percentage loss.

The relationship between portfolio performance (IRR) and frequency of loss is depicted in Figure 2. The location of the all-cash portfolio at the far right is instructive. Even though cash always has positive nominal returns, as the sole asset in a retirement distribution portfolio, it exposes retirees to annual losses over 50 percent of the time. The seven-asset portfolios (EW and CW) and the six-asset portfolio (#6 dot) represent ideal allocation models for postretirement distribution portfolios given their location closest to the northwest corner of the graph.

Achieving low standard deviation of return is a worthy goal, but should not be the primary goal in an accumulation portfolio or a distribution portfolio. Rather, achieving low aggregate portfolio correlation should be the primary goal. In an accumulation portfolio, creating diverse seven-asset portfolios (equal-weighted or custom-weighted) was shown to produce superior risk-adjusted performance. Moreover, losses over any three-year period were eliminated in the EW and CW portfolios.

In a retirement distribution portfolio, this analysis has demonstrated that successively adding equity assets to a fixed-income portfolio causes standard deviation of return to increase, but also dramatically lowers the frequency of portfolio losses. Portfolio losses are hard to ignore, whereas standard deviation of return is a more abstract concept.

The performance of the distribution portfolio improved and the aggregate portfolio correlation generally declined or held steady as each additional asset was added. Performance and aggregate correlation improved dramatically when the seventh asset (in this case, commodities) was added. Of the assets analyzed in this study, commodities are the only asset class that has consistently negative correlations with all the other asset classes. Consequently, it is the low correlation of commodities that generated a host of portfolio benefits, rather than simply being the last asset added.

Considering all the measures in this analysis (IRR, standard deviation, aggregate portfolio correlation, worst-case one-year loss, frequency of loss and average percentage annual loss), the ideal postretirement distribution portfolio is the CW portfolio. The EW portfolio is the best allocation model during the preretirement accumulation phase.

As shown by the mathematics of recovery for portfolios in withdrawal mode, avoiding large losses is of paramount importance. Compared with a "classic"; conservative 40 percent equity/60 percent fixed-income portfolio, the CW portfolio had a 32 bps higher return, 210 bps lower standard deviation of return, lower aggregate correlation (0.13 versus 0.22), dramatically lower worst-case loss (-7.3 percent versus -12.2 percent), lower frequency of loss (16 percent versus 21 percent) and lower average annual loss (-2.6 percent versus -4.7 percent).

Achieving low correlation among the assets in a portfolio is the key to generating a multitude of benefits. However, it requires the use of several assets that have low correlation with each other. Some of these "low-correlation"; assets may not fit the traditional paradigm of assets to be included in a retirement portfolio. Some paradigms need to change.


Bernstein, W., 2001, The Intelligent Asset Allocator, McGraw Hill

Markowitz, H., 1991, Portfolio Selection, Blackwell Publishing


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