Fast casual dining has been a growth area for the restaurant industry in recent years. The concept--fresh, high-quality food at a reasonable price--has attracted diners searching for a convenient, cost-effective way to eat well on the go. One popular aspect of many fast-casual dining restaurants is the high degree of personalization available. Consider the proliferation of chopped salad chains, where you can order from a preset menu of chef-designed salads or build your own, choosing from several types of lettuce and a diverse array of toppings that offer distinct flavor and nutrition profiles. Having so many options gives you control over the outcome and results in a meal with a satisfying mix of different textures and flavors.
Smart beta portfolios offer a similar level of optionality but, in this case, the high-quality ingredients are factors that offer unique characteristics and can be combined in different configurations to produce desired outcomes. As we noted in a previous blog, it is generally accepted that there are six key factors in the equity market--Value, Quality, Size, Low Volatility, Momentum and Yield. We highlighted that these factors have distinct fundamental characteristics based on what they seek to identify at the individual stock level.
Attractive Relative Performance Can Improve Investment Outcomes
Each of the six factors has a history of delivering improved risk-adjusted returns compared with the market, as represented by the Russell 1000 Index. Between June 2001 and September 2017, the Sharpe Ratio of the Russell 1000 was a respectable 0.45. As Exhibit 1 highlights, all six factors offered better Sharpe Ratios than the index. Among them, Momentum delivered the weakest return per unit of risk at 0.48—still an improvement over the index— while Quality’s Sharpe Ratio came in at 0.58, driven by both better returns and lower risk. Interestingly, the Size factor had the most robust performance for the quarter, but also the highest standard deviation. On the flip side, Volatility had the lowest standard deviation along with the lowest up capture, but also the second lowest down capture.
Exhibit 1: Factors Have Delivered Strong Returns Relative to the Market
| Return | Standard Deviation | Sharpe Ratio | Up Capture Ratio | Down Capture Ratio | |
| Russell 1000 Momentum Factor Index | 7.18% | 13.74 | 0.48 | 97.50 | 95.02 |
| Russell 1000 Quality Factor Index | 8.35 | 13.04 | 0.58 | 95.23 | 85.19 |
| Russell 1000 Size Factor Index | 9.95 | 17.14 | 0.56 | 120.22 | 110.40 |
| Russell 1000 Value Factor Index | 8.43 | 15.37 | 0.52 | 105.92 | 99.43 |
| Russell 1000 Volatility Factor Index | 7.02 | 12.27 | 0.51 | 85.43 | 79.28 |
| Russell 1000 Yield Factor Index | 7.98 | 13.04 | 0.55 | 88.60 | 78.10 |
| Russell 1000 Index | 6.92 | 14.40 | 0.45 | 100.00 | 100.00 |
Sources: FTSE Russell, Morningstar, OppenheimerFunds, Inc., time period includes 7/1/01 to 9/30/17. Past performance is no guarantee of future results. Charts and graphs are provided for illustrative purposes only. Index returns shown may not represent the results of the actual trading of investable assets. Certain returns shown may reflect backtested performance. All performance presented of the factor indices prior to the index inception date (September 30, 2015) is backtested performance.
There are both behavioral and risk-based reasons why factors can help improve investor outcomes, whether the goal is to enhance performance potential or reduce risk. Let’s examine the Value factor. From a behavioral perspective, investors have a tendency to bid up growth stocks on the assumption that their future prospects are as good as their past results. For this reason, growth stocks are persistently expensive and value stocks are relatively cheap. From a risk-based perspective, because value stocks have greater leverage and lower margins, they may be less adaptable to changing economic and business conditions. In other words, Value may work because humans make mistakes about pricing in future growth and/or the companies themselves are riskier and investors are compensated for taking that risk. (In a future blog, we will examine potential behavioral and risk-based reasons for outperformance for each factor.)
Short-Term Performance Variances Offer Diversification Potential
While all six of these factors have delivered positive long-term, risk-adjusted returns, their performance has varied markedly over shorter time periods (Exhibit 2). Factors may experience periods of material outperformance or underperformance relative to their own history and the market because the macroeconomic backdrop plays an important role in influencing performance. For example, the Value factor outperformed in 2013 and 2016, but underperformed in 2014, 2015 and 2017.
As a result of these performance differentials, factors exhibit low to modest correlation to one another on the basis of excess returns relative to the market (Exhibit 3). The average correlation of the pairs is only 0.06%. Of course, when you combine securities with low correlations to each other in a portfolio, it offers diversification benefits and may decrease volatility.
Exhibit 3: Correlations Among Factors Is Low
| Index Name | 1 | 2 | 3 | 4 | 5 | 6 |
| 1) Russell 1000 Quality Factor Index | 1.00 | |||||
| 2) Russell 1000 Size Factor Index | -0.47 | 1.00 | ||||
| 3) Russell 1000 Yield Factor Index | 0.25 | -0.37 | 1.00 | |||
| 4) Russell 1000 Value Factor Index | -0.31 | 0.36 | 0.35 | 1.00 | ||
| 5) Russell 1000 Volatility Factor Index | 0.54 | -0.62 | 0.82 | -0.05 | 1.00 | |
| 6) Russell 1000 Momentum Factor Index | 0.49 | -0.08 | 0.06 | -0.26 | 0.23 | 1.00 |
Sources: FTSE Russell, Morningstar, OppenheimerFunds, Inc., time period includes 7/1/01 to 9/30/17.
Whether you’re making a salad or assembling a factor-based portfolio, having more control over the end product is generally a good thing. There’s a wide range of possible ways to incorporate factors into an investment strategy. An investor may want to target a combination of factors, such as a cyclical factor and a more defensive factor. Another investor may use a factor to complement existing portfolio holdings, or look to off-the-shelf, multi-factor portfolios —a topic that will be the subject of future blogs. However investors decide to use them, factors offer a low-cost way to exert a degree of control over the fulfillment of their objectives.
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OppenheimerFunds is not undertaking to provide impartial investment advice or to provide advice in a fiduciary capacity.
Mutual funds and exchange traded funds are subject to market risk and volatility. Shares may gain or lose value. Alternative weighting approaches (i.e., using factor weighting as a measure), while designed to enhance potential returns, may not produce the desired results.
Past performance is no guarantee of future results. Charts and graphs are provided for illustrative purposes only. Index returns shown may not represent the results of the actual trading of investable assets. Certain returns shown may reflect backtested performance. All performance presented prior to the index inception date is backtested performance. Backtested performance is not actual performance, but is hypothetical. The backtest calculations are based on the same methodology that was in effect when the index was officially launched. However, backtested data may reflect the application of the index methodology with the benefit of hindsight, and the historic calculations of an index may change from month to month based on revisions to the underlying economic data used in the calculation of the index.
These views represent the opinions of OppenheimerFunds, Inc. and are not intended as investment advice or to predict or depict the performance of any investment. These views are as of the publication date, and are subject to change based on subsequent developments.