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SPXU Is Still A Dangerous Play


  • Leveraged ETFs may have an unpredictable behavior.
  • We show 20+ ETFs as examples.
  • We focus on the historical and recent behavior of SPXU.
  • This idea was discussed in more depth with members of my private investing community, Quantitative Risk & Value. Get started today »

The ProShares UltraPro Short S&P 500 ETF (NYSEARCA:SPXU) is one of the most popular instruments to short the broad market for trading or hedging purposes. However, its daily leverage factor is a source of drift. It must be closely monitored to detect changes in the drift regime. This article explains what "drift" means, quantifies it in more than 20 leveraged ETFs, shows historical data on SPXU, and finally concludes that it is better to avoid it in current market conditions.

Why do leveraged ETFs drift?

Leveraged ETFs often underperform their underlying indexes leveraged by the same factor. This relative decay has several reasons: beta-slippage, roll yield, tracking errors, management fees. Roll yield may be prominent for commodity ETFs, but beta-slippage is usually the main source of decay. However, it doesn’t always result in decay. When an asset is trending with little volatility, a leveraged ETF can bring an excess return over the leveraged asset. You can click here to learn more about beta-slippage and examples.

Monthly and yearly drift watchlist

A few simple formulas and data definitions are necessary before going to the point. “Lev” is the leveraging factor. “Return” is the total return of an ETF (including dividends). “IndexReturn” is the total return of the underlying index, measured on a non-leveraged ETF (also with dividends). “ETFdrift” is the drift of the ETF relative to the leveraged index. “TradeDrift” is the drift relative to an equivalent position in the non-leveraged index. ETFdrift and TradeDrift are calculated as follows, where Abs is the absolute value operator.

ETFdrift = Return - (IndexReturn x Lev)

TradeDrift = ETFdrift / Abs(Lev.)

“Decay” is negative drift. “Month” stands for 21 trading days, “year” for 252 trading days.

A drift is a difference between 2 returns, so it can be below -100%.



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This article was written by

Fred Piard profile picture
Data-driven portfolios and risk indicators.
Author of Quantitative Risk & Value and three books, I have been investing in systematic strategies since 2010. I have a PhD in computer science, an MSc in software engineering, an MSc in civil engineering and 30 years of professional experience in various sectors. My aim is making simple and efficient quantitative investing techniques available to my followers. Quantitative models can make investment decisions faster, reproducible and emotionless by focusing on relevant information in the middle of market noise. Moreover, models can be refined to meet specific risk tolerance and objectives. 

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I am an individual investor and an IT professional, not a finance professional. My writings are data analysis and opinions, not investment advice. They may contain inaccurate information, despite all the effort I put in them. Readers are responsible for all consequences of using information included in my work, and are encouraged to do their own research from various sources.

Analyst’s Disclosure: I am/we are long TLT. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.

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