Paul Docherty, a senior lecturer at Newcastle Business School. University of Newcastle, in Australia, has studied the performance of the factors that underlie smart beta portfolios within the equity markets of that country.

On the basis of a long time-series of data, Docherty has concluded that four such factors “all generate positive abnormal returns” in those markets: value, momentum, low vol, and quality. Diversifying across these four factors is the smart way to make use of smart beta, he thinks.

The other factor in the usual list of five is size. Since Rolf W. Banz’ work in 1981, there has been speculation that small firms generate greater return than do larger firms after controlling for risk. But Docherty can’t find evidence for this is Australia. After accounting for illiquidity and transaction costs, the remaining size effect” is insignificant. “Not an investable anomaly,” he says. This is in accord with recent international findings.

But with the other four smart-beta factors?

Value refers to the book-to-market ratio. This is also known as the HML ratio, from the phrase
“high minus low” given the Fama-French argument that companies with high book-to-market ratios (value stocks) outperform those with low ratios (growth stocks). Docherty mentions that there are several other ways to measure “value” aside from book-to-market. One might use the P/E ratio, for example, or compare cash flow to price. But book-to-market “is the superior proxy for value in the Australian equity market.”

The HML ratio has had a good run over most of the sample period Docherty employs, beginning in 1990, and its cumulative returns across time are impressive, but it’s important to observe that “there is an evident reduction in the gradient of the cumulative returns in recent years.”

Performance of the WML factor in Australia

Mean St. Dev. T-Strat Sharpe Ratio Hit Rate Max Drawdown
1991-2015 1.29% 5.19% 4.27 0.25 63% -19.96%
1991-1995 0.31% 3.53% 0.68 0.09 53.3% -7.98%
1996-2000 1.15% 5.28% 1.68 0.22 65% -19.96%
2001-2005 2.61% 5.12% 3.95 0.51 71.7% -8.51%
2006-2010 0.89% 6.53% 1.06 0.14 61.7% -13.68%
2011-2015 1.37% 4.80% 2.15 0.28 64.9% -13.41%

Source: Docherty, “How smart is smart beta investing?” Table 3.

Moving on … the momentum factor (or “winner-minus-loser”, that is, WML) is the best documented anomaly of the traditional five. Docherty cites a recent study by Vanstone and Hahn that reports that “the capacity of momentum investing in Australia is sufficiently large in dollar terms to support its practical implementation as an investment strategy.”

Low vol has been under discussion as a factor in above-normal returns since a seminal paper by Black, Jensen, and Scholes in 1972. The notion of a low vol premium by definition implies that the actual security market line is much flatter than the one predicted by the Capital Asset Pricing Model.

Significant Drawdowns

Docherty’s data indicates that the mean monthly return on the Vol factor in Australian markets is 1.45%, the highest monthly return of any of the five factors he looked at. Both the Vol factor and WML share one drawback, each has seen significant drawdowns. The max drawdown for the Vol factor in Australia over the covered period in 25.56%.

Then there is quality, or quality-minus-junk (QMJ). As in all fields, “quality” in the realm of capital assets is a tricky thing to define. As Docherty understands it the term refers to asset growth and accruals (negatively) as well as to corporate governance and profitability (on the positive side). Quality as so understood has “relatively modest returns compared with other smart beta factors,” he finds, but it does provide a hedge against downturns in broad market movements.

What is most intriguing about Docherty’s numbers is that the correlations among the factors he discusses “are quite low and, in many cases, negative.” Given this situation , the real question is not whether smart beta is smart (it is) or which factor is smartest (that depends on where one is in the business cycle, and other matters) but what mix of the four (or, if one wants to continue including size) what mix of the five factors is optimal.