As more money managers help expand the exchange traded fund universe, investors are now able to capitalize on established management team's research capabilities and investment styles.
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For example, the Fidelity Low Volatility Factor ETF (NYSEArca: FDLO), Fidelity Momentum Factor ETF (NYSEArca: FDMO), Fidelity Quality Factor ETF (NYSEArca: FQAL), Fidelity Value Factor ETF (NYSEArca: FVAL) and Fidelity Core Dividend ETF (NYSEArca: FDVV) are five ETFs that leverage decades of analysts and research out of Fidelity's quant team, Darby Nielson, managing director of research at Fidelity Management & Research Company, told ETF Trends in a call.
The individual factors that are implemented within the smart beta ETF options were selected from Fidelity's 3,000 factor library. Fidelity has engaged in factor analysis and stock fundamental stock picking, with 50 years under the belt of its quant research division.
Fidelity's recently launched factor-based ETF suite selects components based on over 10 years of analysis from its factor models.The World of ETFs...
"The factor suite is based on fundamental factors leveraged on over 10-plus years of research," Nielson said. "They are outcome oriented."
Smart beta ETFs have only recently come into focus in the financial world, but the underlying investment philosophy has been around for decades. In the traditional open-end mutual fund space, many strategies have relied on factors, and it is only recently that these same factors have been brought over to the ETF side.
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A factor, simply put, is an attribute that may help explain risk and returns. For example, over the years, academics and investment professionals have identified a number of factors that have historically outperformed the broader market or diminished a portfolio's risk over time, including the size factor that focuses on outperformance in small-cap stocks, value factor that show inexpensive stocks have usually outperformed, momentum that shows stocks have outperforme din the medium term will continue to do so, quality that reflects companies with strong staying power and low volatility that may produce higher risk-adjusted returns.
"The factors provide high intended exposure and low unintended exposure," Nielson said. "You buy what you want."
For example, Fidelity's suite of single-factor ETFs focus on a single intended exposure. FDLO covers large- and mid-cap U.S. companies that exhibit lower volatility than the broader market. Holdings include those that show historically low volatility of returns, low beta (a measure of market sensitivity) and low earnings volatility.
FDMO includes large- and mid-cap U.S. companies that exhibit positive momentum signals. Companies include those with historically high total and volatility-adjusted returns, high positive earnings surprises and low average short interest.
FQAL follows large- and mid-cap U.S. companies with higher quality profiles than the broader market. The underlying index focuses on companies with historically high free–cash-flow margins, high returns on invested capital and high-free-cash flow stability.
FVAL covers large- and mid-cap U.S. companies that have attractive valuations. Components exhibit historically high free-cash-flow yields, low enterprise value to EBITDA (earnings before interest, taxes, depreciation and amortization), low price to tangible book value and low price to future earnings.
FDVV is designed to reflect the performance of stocks of large- and mid-capitalization dividend-paying companies that are expected to continue to pay and grow their dividends.
These single factors, which were traditionally found on the actively managed side of Fidelity's business, have now been imported into its ETF business, providing investors with exposure to Fidelity's intellectual property or research in a passive, low-cost fund wrapper.
"The factor ETFs are active by design, passive by implementation," Nielson added.
This article was provided courtesy of our partners at etftrends.com.
Our editors found this article on this site using Google and regenerated it for our readers.
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