Rick Welch: Dollars and $ense
Smart Beta and Factors
Smart beta is a framework for portfolio asset allocation that moves away from the traditional market-cap weighted approach towards alternative weightings (based on factors) with the goal of improving investment performance and portfolio diversification. In this framework, the portfolio building blocks are factors, rather than asset classes. The difference here is that factors are underlying drivers of risk and return while asset classes are merely groupings of similar types of assets. Factors can be thought of as characteristics of investment assets that are important to explain their risk and price return performance. The theory behind factor investing is that the performance of any portfolio of stocks (or bonds) is directly related to a small number of factors, so the investing process can be improved by isolating and focusing on those very same factors. When we organize a portfolio of assets along the lines of underlying risk we get a better understanding of how the trade-off between risk and return impacts investment performance.
Examples of equity or stock factors include three defensive oriented factors, like low volatility, quality and dividend, and three cyclical factors, like momentum, value, and size. From a correlation perspective with the S&P 500, each of these factors have correlations between 0.73 and 0.94. While low volatility and dividend are self-explanatory, a quality factor is based on the financial strength of a company using measures like return-on-equity, earnings stability, balance sheet strength and financial leverage. Momentum stocks exhibit a persistence (or provide an identifiable trend) to outperform other stocks, which tendency is typically based on 12-month relative returns. We have previously written about value stocks (also known as cheaper stocks) which typically have low price-to-book and price-to-earnings ratios which suggest that future positive price movement is possible. When an index is based on a size factor, all companies included therein are equally weighted, in contrast to the more traditional method of market-cap (large, medium and small) weighting. Factors can be used to construct a full range of risk profile asset allocation models including conservative (use quality and low volatility factors), income oriented (dividend and value factors) and aggressive (momentum and size factors).
While factor analysis offers great insight to investors, it is not without its challenges. For example, there is no universal agreement on what factors are most important to predicting price performance for stocks and bonds. To the list of the previously described factors, we would certainly add interest rates and inflation. One study that we used for this article said it best with this suggestion. “The right factors to consider depends a great deal on what questions you are trying to answer.” It is important to remember that different factors tend to outperform in different market environments. The same study also found that while single-factor strategies often outperformed the market over the long term, that there can be long periods of time in which they underperform. While the returns from the most widely used factors have proven to be consistent over time, it is noted that those returns show a wide degree of variation across all factors. With this in mind, multiple or blended factor strategies with well-timed tactical adjustments might be preferred. Diversifying factors can provide the broad exposure needed to address the problem associated with ever changing market and economic conditions.