A Different Way for ETF Investors to Tap Into the Market | Page 2 of 2 | ETF Trends

The new funds break down the universe of securities into investment categories based on sectors and countries. The five-year return patterns of the countries and sectors are taken to uncover relationships – areas that behave alike or differently. The index then combines investment categories with more highly correlated historical performance into smaller number of so-called clusters, which are categorized based on tendency to behave similarly, or show various correlations. Each of these clusters are then equally weighted individually and also equally weighted across the portfolio to produce a diversified investment strategy.

Consequently, through the DBI approach, the group of global stock ETFs should exhibit low correlation of excess return to active stock managers and traditional market cap-weighted indices. The DBI methodology also helps diminish concentration risk within country and sector exposures. For instance, UDBI is currently underweight energy at 2.3% and materials at 3.6%, two areas that are struggling in a low commodity environment, while overweighting consumer staples 18.1% and consumer discretionary 18.1%.

Additionally, the Legg Mason Low Volatility High Dividend ETF (NasdaqGM: LVHD) should help investors who are seeking new sources of yield in a changing market environment. Currently, fixed-income investors would increase exposure to credit risk to generate greater yields, or investors could look to riskier dividend-paying stocks like master limited partnerships, but these high-yield areas expose people to greater risks.

“LVHD identifies higher dividend payers but only companies that are able to afford the dividends,” Michael J. LaBella, Portfolio Manager at Legg Mason, told ETF Trends.

Specifically, LVHD focuses on U.S. equity stocks with relatively high yield and low price and earnings volatility, and the fund also targets profitable companies. The ideas is that a stock’s ability to sustain strong dividends is associated with lower volatility.

Max Chen contributed to this article.