Can you use Inverse ETFs to Trade the S&P 500?

Using Normalized Relative Volume to measure market risk

In 2018, I wrote a paper on an indicator I created called Normalized Relative Volume. I’ll share the paper in the future; it was published in the Journal of Technical Analysis in 2020.

In 2016, I was thinking about how Normalized Relative Volume could be used as a sentiment indicator to define when investors were relatively fearful or greedy. I decided that Inverse ETFs, ETFs that go up in price when the stock market goes down, were a suitable security to use a base to measure my volume on. Since my audience is still really small, and I know you’re all pretty sophisticated, I won’t go into what an Inverse ETF is, how it works, or what volume is! We’ll cover all of that in the future.

In fact, I’m copying this post from one I made to a group of professional analysts. Apologies if it’s missing any background information. Let me know what questions you have and I’ll try to update the post later to add anything I missed.

The rest of this post will show you how I use Normalized Relative Volume on inverse ETFs to determine whether the stock market is more or less risky.

This is for informational purposes only. I’m not an investment advisor and don’t know anything about your investment needs.

Also, this will get a little wonky. But I had fun writing it.

Also, there is no car content in this one. I’ll make it up to you.

Normalized Relative Volume (NRV) on Inverse ETFs

I recently revisited some data I had pulled in 2016. I think it provides a good out of sample analysis, using data from July 2009 through (mid-)January 2016.

I ran this using Bloomberg data vs. NYSE TVOL as my benchmark in the NRV calculation and summed the volume of several short ETFs (SDS, SPXS, SPXU, SH) rather than using a single security. Again, NRV is calculated as:

I like to normalize volume data, because normalizing it also helps to account for longer-term shifts as well as seasonality. It’s also nice to have it centered around 1

I also like to think of this as a crowd of investors, rather than trading volume. Think about how crowds on the pre-electronic trading NYSE floor would ebb and flow around different posts when there was news in those stocks.

Here’s a chart of my results versus the S&P 500 (SPY):

Some stats:

I looked at the peaks and valleys to see how SPY performed over the following 21 days (1 month).

• Valleys are when relative volume < 0.6 for the first time in 10 days. Low demand for inverse ETFs.

• Peaks are defined as relative volume > 1.75 for the first time in 10 days. Heavy demand for inverse ETFs.

Results:

Valleys: (8 observations)

• Mean 1-month forward return: -1.41%

• Median 1-month forward return: -1.01%

• Percent 1-month forward return that is positive: 25%

Peaks: (4 observations)

• Mean 1-month forward return: 1.88%

• Median 1-month forward return: 3.03%

• Percent 1-month forward return that is positive: 75%

There are probably better ways to do this analysis, but I wanted to keep it simple, so I just used the first cross above or below a particular level. This shows that the indicator works really to highlight low or high risk times to invest.

Next, I looked at month end data to create a scatterplot of forward returns using non-overlapping data. Here’s the scatter:

The red zone is when the NRV < 0.85. The green zone is NRV > 1.15. These levels are different than what I used above, just to include more data in each result.

Statistics for the above:

The slope of the regression line is positive and statistically significant. However, I don’t think there’s really any information when the NRV for inverse ETFs is between about 0.8 and 1.2.

Stats for the red and green zone are as follows:

Summary:

Based on data from July 2009-Jan 2016 (analysis from Jan 2010-Jan2016), there is lots of value in this indicator. When investor demand for inverse ETFs is low, the market will, at best perform normally, but with increased risk of reversal, especially if the NRV drops below 0.6. When investor demand for inverse ETFs is high, there is a strong bias towards the next month returns being positive.

As time permits, I’ll pull more recent data and rerun the analysis.

Again, not a trading system and I’m giving investment advice in this post. Consider this indicator as you do your own analysis.

Let me know what you think!

Jason