Shirbini says that it isn’t enough to choose factors based on rigorous academic research—the measures of those factors must match the measures used within the research.
“Academic research tends to use simple measures to determine whether there is a risk premium,” Shirbini says. “For example, with value Fama and French used book-to-market, one simple measure of value. With momentum, we use the 12 month price momentum measure that several researchers have used. With volatility, we look at volatility over the past two years." And for size, Scientific Beta selects stocks from the lowest to the highest market capitalization.
Using the S&P 500 as a starting point, within the Global X Scientific Beta U.S. ETF, the value index selects the lowest 250 stocks by price-to-book, the size index the smallest 250 stocks by market cap, the momentum index the highest 250 stocks by 12-month returns, and the low-volatility index the lowest 250 stocks by 104 week volatility.
“Sometimes we see people creating their own definitions for factors or focused on accessing factors without thinking about diversification,” Jacobs says. “It’s not just overall performance that we need to consider when designing products. It’s also risk-adjusted returns.”
After the stocks are selected, each index uses a multi-strategy weighting scheme to diversify and address potential concentration risks and other model-specific risks. The stocks are equal-weighted to minimize concentration, then volatility is minimized through decorrelation, risk weighting and the efficient maximum Sharpe ratio.
“We construct indexes that give you exposure to each one of these factors separately,” Shirbini says. “The final step in the process is to combine these four factors into one product and to create what we call a multi-factor index. These indexes are attractive because they smooth out the returns over time.”
Shirbini says turnover is limited because some of the trades that might be incurred by investing using a single-factor strategy end up being eliminated.
“The way we construct these multi-factor indexes gives you a great deal of transparency,” Shirbini says. “You can look at each individual component and understand your investment, which factor is working at which time. It makes the process easy to break down.”
While the EDHEC strategy might sound complicated, Shirbini says at heart it’s just a combination of simple measures working in tandem that should lead to smart beta’s end point: capturing the heart of the market’s positive performance while limiting risks.
That simplicity is key to the Global X products’ performance through volatility. At the end of March, the fund had generated three-month cumulative returns of 7 percent, compared with 1.35 percent for the S&P 500 index.