With an energy rally underway thanks to strong oil prices and a keen interest in renewable sources, ETF investors can get a factor-based strategy in the sector using the John Hancock Multifactor Energy ETF (JHME), which is up 20% year-to-date.
JHME seeks to provide investment results that closely correspond, before fees and expenses, to the performance of the John Hancock Dimensional Energy Index (the index). The fund normally invests at least 80% of its net assets (plus any borrowings for investment purposes) in securities that compose the fund’s index.
The index is designed to comprise securities in the energy sector within the U.S. Universe whose market capitalizations are larger than that of the 1001st largest U.S. company at the time of reconstitution. The fund is up 30% within the last six months.
Overall, the fund provides investors with:
- Broad Energy Stock Exposure: JHME targets a wide range of U.S. energy stocks to access the breadth of the sector’s opportunities.
- A Time-Tested Multi-Factor Approach: The ETF emphasizes factors (smaller cap, lower relative price, and higher profitability) that academic research has linked to higher expected returns.
- Efficient Structure: The fund seeks to minimize turnover, trading costs, tax liabilities, and cash drag.
Why to Use a Multi-Factor Strategy
One of the obvious advantages of using a multi-factor strategy is that an investor is never too exposed to one factor in a given market environment. A multi-factor approach gives investors balanced exposure.
“Multifactor investing is when investors use more than one of the attributes in an investment strategy,” a Wall Street Journal report said. “The purpose of combining such characteristics is to achieve ‘more consistent performance through time,’ says a recent report from Russell. ‘When one factor is underperforming, another factor may be outperforming.'”
The energy sector is an exemplary breeding ground for JHME’s multi-factor strategy. The sector can be sensitive to sudden changes to economic factors like demand, making a factor-based strategy that incorporates value or quality optimal in certain cases.
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