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DGAZ And Leveraged ETF Performance Analysis

|Includes: VelocityShares 3x Inverse Natural Gas ETN (DGAZ), UGAZ

DGAZ and Leveraged ETF Performance Analysis

Many investors have heard the mention of "decay" on leveraged ETF investments versus their underlying benchmarks and much fear is often placed in the minds of investors thinking they might do anything other than day trade 2x or 3x leveraged ETF's. In this article, I plan to share my journey to learn more about the performance characteristics of leveraged ETF's and seek to identify a compounding phenomenon I have witnessed in my own leveraged ETF trading and observations over time.

Case Study on Leveraged ETF Performance

For those interested in the mathematical modeling of leveraged ETF's and conclusions from a study that reflected some of the following conclusions:

  1. 1 month period holding a leveraged ETF's should provide a very tight correlation to expectations against the benchmarks
  2. 1 quarter and 1 year periods, the ETF performance against the benchmarks breaks down (2x or 3x leveraged funds do not perform to a tight correlation to the benchmark)

Here is a link to the paper, "Long Term Performance of Leveraged ETF's", I think makes for an interesting read - here.

Decay or Beta Slippage on Leveraged ETFs

Most of us have seen the calculations used to communicate beta slippage or decay in leveraged ETFs, an example pasted in below:

Assume a volatile underlying benchmark goes up 25% one day and down 20% the following day. A 2x leveraged ETF goes up 50% the first day and down 40% the second day. On the close of the second day, the underlying asset is back to its initial price:

(1 + 0.25) x (1 - 0.2) = 1

The 2x leveraged ETF, however, loses some value called decay, or beta slippage

(1 + 0.5) x (1 - 0.4) = 0.9

DGAZ and UGAZ 3x Leveraged Performance Analysis

In this section, I want to explore further, the performance characteristics of these ETF's against the benchmark S&P Natural Gas Index and the Natural Gas spot price for analysis and extending to conclusions resulting from that analysis.

I have written two prior articles on DGAZ/UGAZ that can be referenced for trade target analysis associated with my investment thesis and Risk Analysis associated with that trade thesis:

  1. DGAZ Trade Target: Here
  2. DGAZ Risk Analysis: Here

Based on information from the above articles, lets look at some performance characteristics associated with DGAZ. First, here is a DGAZ chart with overlay of UGAZ I used for the analysis associated with my thesis.

From the chart, I studied the cycle of the 1st spread indicated by the first 3 vertical lines on the chart at the beginning of the cycle, middle of cycle (at the maximum spread), and at the end of the cycle. In the model, I used closing prices of each. For Natural Gas and the S&P Natural Gas Index, I referenced charts for those as well, pasted in below.

Natural Gas:

S&P Natural Gas Index (1 year):

From these sources, I have plotted the closing prices in the table below, then calculated and provided the performance characteristics.

Pricing at inflection points - Spread Cycle 1





NG Index
















  1. Price movement behavior from 2/15 to 5/1 max spread:
  2. DGAZ - (60%) UGAZ - 213% NG 27% NGI - 31%
  3. Price movement behavior from the 5/1 spread to the crossover on 8/9:
  4. DGAZ - 210% UGAZ - (38.2%) NG - (20%) NGI - (26.7%)

Analysis of the Performance Data:

From the conclusions of the Case Study and the beta slippage formula, one would expect a nearly 3-month performance of DGAZ to break down and not meet the 2x performance of the S&P NG Index. But what happened in the cycle from max spread to closure of the spread cycle?

The S&P NG Index performance was (26.7%). One would anticipate that DGAZ performance at 3x inverse of this would be 26.7% x 3 = 80.1%. Yet, DGAZ in fact returned 210%! This yield produced well over 2 times what our expectations would have been.

So, where did the beta slippage/decay go that everyone is so worried about? Where did our breakdown in performance of the 3x leveraged ETF holding for longer than 1 month go?

This is the powerful phenomenon I have experienced and observed in leveraged ETF performance characteristics that just does not jive with what many communicate about leveraged ETF's. Now believe me, I'm not saying beta slippage and decay are not a factor. I have had some bad experiences when the trend goes the wrong direction from my investments in having ETF performance work rapidly against one, with a clear view of the damage beta slippage can inflict. But, when the trend is aligned with the investment, something magical appears to be happening to the return that is not explained by the math.

My hunches for further exploration:

ETF's like stocks, trade at what investors and traders will pay for them - and this can separate from Net Asset Value which would correlate to the expected performance versus the benchmark. When investor and trader sentiment is working against the trend, trading price values may be pushed below NAV or down closer to NAV, and when sentiment is with the trend, we may have a tendency to price above NAV and/or expand the price versus NAV. This would be similar to how stocks trade at differing multiples on Book Value or PE ratios offering a compounding positive or negative effect on pricing.

NAV versus Market Price Comparison:

From Fidelity's website, I found the following table which seems to support at least a portion for my hunch. Notice there are some significant variances between market return and NAV return.

Cumulative Total Returns AS OF 01/29/2014


NAV Return

Market Return

S&P 500 Index





4 Weeks




13 Weeks




26 Weeks




So now, I know the price performance for the period reviewed was 210%. What I would be interested in finding out next is 1) What is the NAV performance over the same period and 2) is there a way for me to chart price and NAV comparisons on a standard 1 year, 3 month etc. chart. I have done some searches on the internet, but so far, have not found what I am looking for to be able to do this.

What this will help me to discover is:

  1. whether all of the premium in price performance is associated with premium over NAV
  2. or whether NAV compounds to outperform in the period to account for some of the over performance
  3. or, whether some other variable(s) comes into play


  1. For now, one conclusion is that beta slippage and decay, while certainly being factors associated with NAV when price trends are moving against a long or inverse leveraged ETF, they cannot account for the performance that can be achieved or the targets for performance for a period without understanding these other variables and forces
  2. We need a good tool for charting ETF market prices versus NAV to be able to understand the relationships of premium or discount over time and its effect on performance. Once we have this, we can then look for whether this explains the entire performance variance, or whether there are other variables at play as well.
  3. DGAZ price targets and performance, or for that matter, price targets and performance of any 2x or 3x leveraged fund cannot be achieved by NAV calculations (including decay/beta slippage) alone and the case study and associated mathematics are only applicable to NAV performance.

If anyone knows of a good tool to help chart price performance versus NAV over time to study these relationships, this may help shorten my quest for more information. Otherwise, I will continue my search to find an appropriate tool. And, as I satisfy my own learning associated with where this additional performance (that could effect one negatively or positively), comes from and all the variables, I will share the progress.

Disclosure: I am long DGAZ.

Additional disclosure: I may trade and reposition DGAZ shares based on dynamics associated with the Natural Gas Market. I may also trade in and out of UGAZ, or buy/sell calls and puts on BOIL or KOLD (2X Leveraged ETFs on Natural Gas Index).The thoughts and opinions in this article, along with all stock talk posts made by the Author, are my own and are shared on the basis of helping others learn, to provoke other points of view that help us all on our journey to become better investors. My posts are never intended to provide investment advice. Investors should always view multiple sources of information in their due diligence process.