Multifactor tilts are best bet for performance boost

Investors have successfully employed style factor tilts for more than 40 years to improve on passive capitalization-weighted equity portfolios. Empirical studies of popular style tilts like value, small size and momentum repeatedly have been shown to outperform benchmarks across most global markets. Because these results are inconsistent with the classic notion that return is a function of risk alone, they are considered anomalous.

Our research confirms that many factor tilts have indeed outperformed their benchmarks in domestic, international and even emerging markets. However, the excess return generated by “pure” single-factor tilts has, with few exceptions, not been entirely consistent across time. In contrast, many multifactor tilts (high quality and low volatility, for example) are shown to both outperform and have persistent excess return. For this reason, investors should seek out products with multifactor exposure to minimize the possibility of extended periods of negative performance.

Northern Trust ranks all stocks on a monthly basis in their respective universes based on individual style factors and places them into quintiles, measuring the subsequent one-month return for each quintile. Table 1 shows the average annualized returns for the highest and lowest quintile for each style factor, the Sharpe ratio, and the average annualized return and Sharpe ratio for the Russell 3000 index, as a representative benchmark. The number in the column under the index name represents the average for all quintiles.

In the United States, the average annual equally weighted return of the Russell 3000 from 1979 to 2012 was 12.9% with a Sharpe ratio of 0.77. However, during this period a tilt toward any of the factors we examined — value, size, momentum, volatility, dividend yield or Northern Trust's proprietary quality factor — would have performed significantly better in terms of both absolute return and Sharpe ratio. (Northern Trust's quality factor is based on research showing that top-quality companies — as defined by a core quality philosophy based on an assessment of management efficiency and profitability — typically outperformed the market with lower volatility.)

Continuing our example, note that the highest value, i.e. cheapest, quintile of stocks earned an average annual return of 16.3% with a Sharpe ratio of 0.86. While this seems like a modest improvement over the index, recall that this represents an average annual outperformance of 3.4% per year for 34 years.

Although not shown, similar results hold for both international developed and emerging markets. In general, tilts toward higher value (cheap), momentum, dividend yield and quality and tilts toward lower volatility and size (small caps) would have produced returns that exceed their benchmarks with a lower level of total risk.

However, there is no reason we must limit ourselves to a tilt toward a single factor. A multifactor approach can produce returns that exceed any single factor individually. For example, the top 20% of stocks at the intersection of high quality and high-dividend yield earn an average annual return of 20.5%, which is considerably greater than the returns to the top-quality quintile (19%) or the top-dividend-yield quintile (15.2%) on their own. Similarly, the top 20% of stocks at the intersection of quality and value earned an annual average return of 23.8%, quality and low volatility earned 21.1%, and quality small caps earned 21.7%, all well in excess of singular factors.

While these results support the case for factor tilts, they do not tell the whole story. Equally important are the pattern and consistency of factor returns. Specifically, we want to be sure that the favorable performance of factor tilts isn't due to a few brief periods in history and that we don't run the risk of protracted intervals of poor performance.

To address this issue, we used the same datasets described above to create “factor mimicking portfolios” for the Russell 3000 in the traditional style. Each month we sorted stocks into quintiles based on their exposure to individual factors, buying the highest Sharpe ratio quintile and selling short the lowest quintile. In this way, we attempted to capture the “pure” return of the factor net of aggregate market activity.

Performance results for these mimicking portfolios are shown in Table 2. The highlighted figures indicate five-year periods in which the factor had negative performance and, hence, during which a tilt toward that factor would have likely underperformed its benchmark. Most factors have several such periods: Small caps, for example, suffered a 15-year stretch from 1984 to 1998 during which the small-size factor underperforms. Likewise, dividend yield, value and low volatility each have two five-year periods (out of the seven analyzed) with negative factor performance. These factor return “cycles” are well documented in the financial literature and suggest there is indeed some timing risk for many factor tilts.

However, the quality metric and all the multifactor tilts have consistent positive returns across all periods. We also see that including quality in multifactor tilts increases the Sharpe ratio of their single-factor counterparts by at least a multiple of two: value went to 1.06 from 0.4, size to 1.27 from 0.2, low volatility to 0.9 from 0.2 and dividend yield to 0.94 from 0.35. Clearly, quality acts to stabilize returns and smooth out factor cycles, thereby eliminating much of the timing risk and volatility associated with singular factor tilts.

Quality also reduced the frequency and severity of drawdowns. Of the 34 years we analyzed, singular factor tilts had positive performance in about 60% of those years, while quality outperformed more than 90% of the time. By adding quality to multifactor tilts, we increase the percentage of years of positive performance to about 83%. In addition, the average maximum one-month drawdown was reduced to 23.2% for multifactor tilts from 37.5% for single-factor tilts.

Our research shows style factor tilts can outperform traditional benchmarks and do so with lower risk. However, the specific tilts must be chosen wisely. Although value, size, volatility and dividend yield tilts all would have outperformed their benchmarks over the long term, they are subject to timing risk and could potentially expose investors to extended periods of underperformance. However, multifactor tilts that include quality can deliver both higher and more consistent returns, and reduce the frequency and severity of drawdowns. n