Factor Methodology

The regression analysis displayed below is an example of what we believe to be the Achilles’ heel of a market capitalization-weighted index. The Y-axis, or vertical line of the chart, is the 10-year forward-looking return of the S&P 500. The X-axis, or horizontal line, is the price-to-sales ratio of the S&P 500 over each month going back to January 1985. As you can see, when the price-to-sales ratio increases,  the forward 10-year return was lower. However, when the price-to-sales ratio was lower, the forward 10-year return was higher. An index that tends to have increased exposure is weighted by market capitalization increases its exposure to stocks that have increased their market capitalization but not necessarily their sales. This can leave an investor with a portfolio that has a higher price-to-sales multiple, which Global Beta believes lowers the probability of their return potential.

Factor Methodology
10 Year Forward Looking Chart

Data sourced from Factset

We believe that by aligning a portfolio’s exposure aimed at reducing its price-to-sales ratio, an investor has optimal exposure, particularly in uncertain markets. Based on our research, we believe that investors who look to avoid portfolios with higher price-to-sales ratios increase their probability of higher forward-looking returns. Therefore, we constructed a suite of factor-based strategies aimed at providing investors with better price-to-sales ratios relative to their respective peer groups.

Our income strategy, the Global Beta Smart Income ETF (“GBDV”), seeks to track the performance of the Global Beta Smart Income Index. The Index selects companies from the S&P 900 Index by their average 12-month trailing yield in each of the previous four quarters. This not only provides the portfolio with a basket of value-oriented securities, but by considering an average yield over four quarters instead of just its current 12-month trailing yield, it reduces recent price bias. By selecting from the S&P 900 Index, which includes both large-cap and mid-cap securities, the portfolio may have a higher exposure to mid-cap securities compared to its peer group. Our research has shown that mid-cap securities generally have lower price-to-sales ratios than large-cap securities. Finally, and possibly most important, we weight the portfolio by revenue. By revenue weighting the portfolio, we gain more exposure to securities with low price-to-sales ratios.

Our low beta strategy, the Global Beta Low Beta ETF (“GBLO”), seeks to track the performance of the Global Beta Low Beta Factor Index. The index selects companies from the S&P 500 Index by their 12-month trailing beta relative to the S&P 500 Index. This provides us with a portfolio of securities that have a lower correlation to the S&P 500 Index, which can be conducive to securities with lower price-to-sales ratios as the S&P 500 Index experiences extreme momentum. We also revenue weight this portfolio, which allows us with a more concentrated exposure to the lower price-to-sales ratios.

Our growth strategy, the Global Beta Rising Stars ETF (“GBGR”), seeks to track the performance of the FactSet Rising Stars Index. The index selects companies from a universe of the top 3000 NYSE and Nasdaq listed securities that meet market cap and liquidity screens. We also eliminate the top 25% of securities that have the lowest sales growth to expected sales growth ratio. We calculate expected sales growth based on a company’s current price-to-sales ratio and operating margins, annualized over a 10-year period. We believe that this reduces our exposure to overvalued securities. We then score companies based on market share growth, industry growth that they participate in, and their operating margin growth. We believe that our starting universe, coupled with our selection process, provides us exposure to more mid-cap and small-cap securities. As mentioned, our research has shown that mid-cap and small-cap securities have better price-to-sales ratios than large-cap securities.