Global X Adds Emerging Markets To Scientific Beta Suite
Global X Funds is planning to add to its suite of Scientific Beta ETFs with a new fund focusing on emerging markets. According to a January 20 filing with the Securities and Exchange Commission (“SEC”), the Global X Scientific Beta Emerging Markets ETF should begin trading sometime in early April 2016, if not before. Suite of Scientific Beta ETFs Like its other Scientific Beta ETFs, Global X’s Emerging Markets ETF will track a custom index: the Scientific Beta Emerging Multi-Beta Multi-Strategy Equal Risk Contribution Index. The index’s objective is to outperform traditional market capitalization-weighted indexes, with a “limited amount of relative risk.” The index’s components are large- and mid-cap stocks that are highly liquid and trade in and are incorporated or domiciled in an emerging-market country. Index components are selected by applying four factors that have been widely recognized by academic literature to outperform over the long run: Value, Size, Low-Volatility and Momentum. Under normal circumstances, the fund will invest at least 80% of its assets in securities from the index, along with American Depository Receipts (“ADRs”) and Global Depository Receipts (“GDRs”). Global X’s other Scientific Beta ETFs launched on May 12, 2015. They include: Global X Scientific Beta US ETF (NYSEARCA: SCIU ) Global X Scientific Beta Europe ETF (NYSEARCA: SCID ) Global X Scientific Beta Japan ETF (NYSEARCA: SCIJ ) Global X Scientific Beta Asia ex-Japan ETF (NYSEARCA: SCIX ) Above Average Performance For the six months ending January 31, 2016, all four ETFs posted losses – but all four ranked in the top half of their Morningstar categories, too. SCIU and SCID posted respective six-month losses of 7.87% and 9.42%, but ranked in the top 41% and 31%, respectively, of their peers. SCIJ posted the lightest losses at 2.61% and ranked in the top 17%. And SCIX, though it nearly posted the steepest six-month losses at -9.41%, ranked in the top 1% of its Morningstar category for the period under review. Past performance does not necessarily predict future results. Jason Seagraves contributed to this article.