The recent market volatility has given traders a chance to profit from market swings with leveraged and inverse exchange traded funds. However, these high-octane ETFs can magnify losses as well, which is why they’re designed for day traders rather than buy-and-hold investors.
The assets under management in leveraged exchange traded products remains high at $35 billion, with short and ultra-short products accounting for about $22 billion of the total, according to a recent report from Barclays Capital. There is about $1 trillion invested in all ETFs.
Leveragde exchange traded funds and notes allow investors to trade on strategies that return two or three times the normal long or inverse performance of an underlying benchmark.
One of the largest leveraged ETFs is an inverse fund that bets against Treasury bonds: ProShares UltraShort 20+ Year Treasury (TBT).
During volatile markets, like now, investors may capitalize on the quick market movements, especially through leverage strategies that would provide a multiple of the normal returns.
Barclays Capital notes that investors have a choice between two distinct types of leveraged products: Daily reset and static funds.
Daily reset funds will try to reflect 2x or 3x the daily return of an underlying index. The key point is that these funds are based off the daily performance of the underlying index. As a result of daily rebalancing, the multi-day return will not perfectly reflect a 2x or 3x performance of the underlying index. Additionally, the daily reset ETFs may underperform during highly volatile situations and outperform during low volatility.
Static products will provide leveraged returns over a multiple-day period. The return of this type of ETF will try to reflect the stated leverage at trade multiplied by the total return of the underlying benchmark - so, a fund might reflect 2x or 3x performance of an underlying benchmark over a multi-day period. However, a static product will stop trading and will be recalled at the ending net asset value if the NAV dips below a predefined point.
Max Chen contributed to this article.