How Does UVXY Work?

Wednesday, March 18th, 2015 | Vance Harwood

Exchange Trade Fund UVXY and its Exchange Traded Note cousin TVIX are 2X leveraged funds that track short term volatility.  To have a good understanding of UVXY (full name:  Ultra VIX Short-Term Futures ETF) you need to know how it trades, how its value is established, what it tracks, and how ProShares makes money running it.


How does UVXY trade? 

  • For the most part UVXY trades like a stock. It can be bought, sold, or sold short anytime the market is open, including pre-market and after-market time periods.  With an average daily volume of 21 million shares its liquidity is excellent and bid/ask spreads are a penny.
  • It has an active set of options available, with seven weeks’ worth of Weeklys and close to the money strikes every 0.5 points.
  • Like a stock, UVXY’s shares can be split or reverse split. If fact, UVXY reverse split 4 times in its first three years of existence—which may be a record.  The last reverse split was a 4:1 and I’m predicting the next one will be around May-June 2015 and will be a 4:1 ratio also.  See this post for more details.
  • UVXY can be traded in most IRAs / Roth IRAs, although your broker will likely require you to electronically sign a waiver that documents the various risks with this security. Shorting of any security is not allowed in an IRA.


How is UVXY’s value established?

  • Unlike stocks, owning UVXY does not give you a share of a corporation.  There are no sales, no quarterly reports, no profit/loss, no PE ratio, and no prospect of ever getting dividends.  Forget about doing fundamental style analysis on UVXY. While you’re at it forget about technical style analysis too, the price of UVXY is not driven by supply and demand—it’s a small tail on the medium sized VIX futures dog, which itself is dominated by SPX options (notional value > $100 billion).
  • According to its prospectus the value of UVXY is closely tied to twice the daily return of the S&P VIX Short-Term Futurestm  This index manages a hypothetical portfolio of the two nearest to expiration VIX futures contracts.  Every day the index specifies a new mix of VIX futures in that portfolio.  For more information on how the index itself works see this post or the UVXY prospectus.
  • The index is maintained by S&P Dow Jones Indices. The theoretical value of UVXY if it were perfectly tracking 2X the daily returns of the short term index is published every 15 seconds as the “intraday indicative” (IV) value.  Yahoo Finance publishes this quote using the ^UVXY-IV ticker.
  • Wholesalers called “Authorized Participants” (APs) will at times intervene in the market if the trading value of UVXY diverges too much from the IV value.  If UVXY is trading enough below the IV value they start buying large blocks of UVXY—which tends to drive the price up, and if it’s trading above they will short UVXY.  The APs have an agreement with ProShares that allows them to do these restorative maneuvers at a profit, so they are highly motivated to keep UVXY’s tracking in good shape.


What does UVXY track?

  • Ideally UVXY would exactly track the CBOE’s VIX® index—the market’s de facto volatility indicator.  However since there are no investments available that directly track the VIX ProShares chose to track the next best choice: VIX futures.
  • VIX Futures are not as volatile as the VIX itself; solutions (e.g., like VXX) that hold unleveraged positions in VIX futures only move about 55% as much as the VIX. This shortfall leaves volatility junkies clamoring for more—hence the 2X leveraged UVXY and TVIX.
  • ProShares achieves the 2X daily return by taking advantage of the fact that VIX futures only require a small percentage (e.g. typically less than 25%) of their face value be deposited as margin to purchase the contract.  By doubling up the number of contracts they own they can double the returns.  To keep this leverage near a constant 2X they have to adjust the number of futures contracts held by the fund at the end of every trading day.  This adjustment is essentially a compounding process.
  • If you want to understand how 2X leveraged funds work in detail you should read this post, but in brief you should know that the 2X leverage only applies to daily percentage returns, not longer term returns. Longer term results depend on the volatility of the market and general trends.  In UVXY’s case these factors usually (but not always) conspire to dramatically drag down its price when held for more than a few days.
  • The leverage process isn’t the only drag on UVXY’s price. The VIX futures used as the underlying carry their own set of problems. The worst being horrific value decay over time.  Most days both sets of VIX futures that UVXY tracks drift lower relative to the VIX—dragging down UVXY’s underling non-leveraged index at the average rate of 7.5% per month (60% per year).  This drag is called roll or contango loss.
  • The combination of losses due to the 2X structure and contango losses add up to typical UVXY losses of 12.5% per month (80% per year). This is not a buy and hold investment.
  • On the other hand, UVXY does a good job of matching the short term percentage moves of the VIX. The chart below shows historical correlations with the linear best-fit approximation showing UVXY’s moves to be about 92% of the VIX’s.    The data from before UVXY’s inception on October 3, 2011 comes from my simulation of UVXY based on the underlying VIX futures.



  • Most people buy UVXY as a contrarian investment, expecting it to go up when the equities market goes down.  It does a respectable job of this with UVXY’s percentage moves averaging -5.96 times the S&P 500’s percentage move. However 16% of the time UVXY has moved in the same direction as the S&P 500.  So please don’t say that UVXY is broken when it doesn’t happen to move the way you expect.
  • The distribution of UVXY % moves relative to the S&P 500 is shown below:


  • With erratic S&P 500 tracking and heavy price erosion over time, owning UVXY is usually a poor investment. Unless your timing is especially good you will lose money.


How does ProShares make money on UVXY?

  • As an Exchange Trade Fund (ETF) UVXY must explicitly hold the appropriate securities or swaps matching the index it tracks. ProShares does a very nice job of providing visibility into those positions.  The “Daily Holdings” tab of their website shows how many VIX futures contracts are being held.  Because of the 2X nature of the fund the face value of the VIX futures contracts will be very close to twice the net “Other asset / cash” value of the fund.


  • ProShares collects a daily investor fee on UVXY’s assets—on an annualized basis it’s 0.95% per year.  With current assets of $700 million this fee generates around $6 million per year.  That should enough to cover ProShares UVXY costs and be profitable, however I suspect the ProShares’ business model includes revenue from more than just the investor fee.
  • One clue on the ProShares’ business model might be contained in following sentence from UVXY prospectus (page 18):
    “A portion of each VIX Fund’s assets may be held in cash and/or U.S. Treasury securities, agency securities, or other high credit quality short-term fixed-income or similar securities (such as shares of money market funds and collateralized repurchase agreements).”  Agency securities are things like Fannie Mae bonds.  The collateralized repurchase agreements category strikes me a place where ProShares might be getting significantly better than money market rates.  With UVXY currently able to invest around $350 million this could be a significant income stream.
  • According to’s ETF Fund Flows tool, UVXY’s net inflows have been around $1.8 billion since its inception in 2011.  It’s currently worth $700 million, so ProShares has facilitated the destruction of about a billion dollars of customer’s money—so far.  I’m confident the overall destruction trend will continue.
  • UVXY has escaped the negative publicity that Barclays’ VXX and VelocityShares’ TVIX funds have generated, but as it continues to grow in size, and continues to destroy shareholder value at eye watering rates it’s probably a matter of time before UVXY starts getting vilified on its own merits or lack there-of.


UVXY is like a loaded gun, effective when used at the right time, but dangerous if you leave it lying around.

UVXY chart

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How Does VXX’s Daily Roll Work?

Monday, January 19th, 2015 | Vance Harwood

All volatility Exchange Traded Products (ETPs) use indexes that track a mix of two or more months of the CBOE’s VIX Futures.  Calculating this mix is not trivial and has resulted in a lot of bleary eyes—including my own.  My intent with this post is to help you understand, and if you desire accurately compute the key indexes used in VXX and other short term volatility funds using Excel or similar tools.

Why do we need a roll anyway?

If we could directly buy the CBOE’s VIX® index none of this would be necessary.  Unfortunately no one has figured out a cost effective approach so we are forced to use the next best thing—VIX Futures.  Like options, VIX futures have fixed expiration dates so volatility indexes need a process of rotating their inventory of futures in order to have consistent exposure to volatility.   This rotation process is evident in the open interest chart below—the next to expire futures being closed out and the next month of futures being opened.


Indexes and Funds—are different things

Before we dive into the details of how this rotation is dealt with, I’d like to address one source of confusion.  ETP’s are not obligated to follow the approach detailed in the indexes.  They are allowed to use other approaches (e.g., over-the-counter swaps) in their efforts to track their indexes.  When ETPs are working properly, their prices closely track the index they specify in their prospectus minus their fees that are deducted on a daily basis.

Because indexes are theoretical constructs they can ignore some practical realities.  For example they implicitly assume fractional VIX futures contracts exist and that the next day’s position can be put in place at market close—even though calculating that position requires market close information.  I’m sure these issues cause headaches for the fund managers, but to their credit the funds usually closely track their index.

The Index Calculation

 The details for the index (ticker SPVXSTR) that VXX tracks are detailed in VXX’s prospectus, pages PS-21 through PS-22. The math is general enough that it covers both the short term index that VXX uses and the midterm index VXZ uses—which adds to its complexity.  The equations use Sigma notation, which probably makes it challenging for people that haven’t studied college level mathematics.   I will present the math below using high school level algebra.

Except for interest calculations all references to days are trading days, excluding market holidays and weekends.

The volatility indexes used by short term volatility ETPs (list of all USA volatility ETPs) utilize the same roll algorithm—at the end of each trading day they systematically reduce the portion of the overall portfolio allocated to the nearest to expiration contracts (which I call M1) and increase the number of the next month’s contracts (M2).

The mix percentages are set by the number of trading days remaining on the M1 contract and the total number of days it’s the next to expire contract (varies between 16 and 25 days).  So if there are 10 days before expiration of the M1 contract out of a total of 21 the mix ratio for M1 will be 10/21 and 11/21 for M2.  At close on the Tuesday before the Wednesday morning M1 expiration there’s no mix because 100% of the portfolio is invested in M2 contracts.

It’s important to understand that the mix is managed as a portfolio dollar value, not by the number of futures contracts.   For example, assume the value at market close of a VIX futures portfolio was $2,020,000, and it was composed of 75 M1 contracts valued at 12 and 80 M2 contracts at 14 (VIX futures contracts have a notional value of $1K times the trading value).   To shift that portfolio to a 9/21 mix for M1 and 12/21 for M2 you should take the entire value of the portfolio and multiply it by 9/21 to get the new dollar allocation for M1, $865,714  (72.14 contracts) and 12/21 times the entire portfolio value to get the dollar allocation for M2,  $1,154,286 (82.45 contracts).

Value weighting gives the index a consistent volatility horizon (e.g., 30 calendar days)—otherwise higher valued futures would be disproportionately weighted.

The next section is for people that want to compute the index themselves.  Yes, there are people that do that.   If you are interested in the supposed “buy high, sell low” theory of roll loss you should check out the “Contango Losses” topic at the bottom of this post.


The Variables

 Lower case “t” stands for the current trading day, “t-1” stands for the previous trading day.

The index level for today ( IndexTRt ) is equal to yesterday’s index (IndexTRt-1) multiplied by a one plus a complex ratio plus the Treasury Bill Return TBRt.  The index creators arbitrarily set the starting value of the index to be 100,000 on December 20th, 2005.

 The number of trading days remaining on the M1 contract is designated by “dr” and the total number of trading days on the M1 contract is “dt.”

M1 and M2 are the daily mark-to market settlement values, not the close values of the VIX futures.  The CBOE provides historical data on VIX futures back to 2004 here.


The Equations

When dr is not equal to dt: 





When dr = dt (the day the previous M1 expires):





Yes, this equation could be simplified, but then it wouldn’t fit as nicely into the equation below which uses a little logic to combine both cases:




The equation assumes that the entire index value is invested in treasury bills.


Contango Losses

  • An interesting special case occurs when you assume that the M1 and M2 prices are completely stable and in a contango term structure for multiple days—for example, M1 at 17 and M2 at 18. In that situation the equation simplifies to:




  • This special case illustrates that there is no erosion of the index value just because it’s selling lower price futures and buying higher priced futures—in fact it goes up because of T-bill interest. It’s the equivalent of exchanging two nickels for a dime—no money is lost.  For more on this see: The Cost of Contango—It’s Not the Daily Roll.

 For more information:

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Near Real Time Graphical VIX Term Structure

Friday, January 16th, 2015 | Vance Harwood

Anyone that follows volatility closely knows that short term views on volatility are much more dynamic than longer term. For example, if the market is moving from a dip into a “V” style recovery the CBOE’s 9 day expectation of volatility VXST, will drop much more than the 30 day VIX.

A chart showing volatility expectations vs time is called a volatility term structure.  The updating chart below uses indexes published by the CBOE to provide up to 6 different points on the current VIX term structure.  The green dots show the numbers published by the CBOE.


The older style VIX calculation (VIXMO) is shown as the black vertical bar and the top of the purple outline around it shows the VIX value.

All VIX style volatility calculations are annualized—they indicate how much the market would be expected to vary in a year if the volatility stayed at that level.  So for example if the volatility number is 15 then the model predicts that the market will stay between +-15% of the current value in the next year with a 68% probability.

The annualization process assumes that volatility drops off with the square root of time. This is a good assumption, however there is a question of what sort of time should you use.  For example the CBOE uses calendar time but I think there is a good case for using the actual amount that the market will be open instead—not counting evenings, weekends and holidays.  The triangles shown on the graph show the CBOE index values annualized with market time instead of calendar time.   Although the two calculations often agree sometimes there are significant deviations.


Additional Resources:

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One Reason Why the New VIX Calculation is Better

Monday, January 12th, 2015 | Vance Harwood

The CBOE changed the way the VIX® was calculated on October 6th, 2014—asserting the change would provide a more accurate assessment of expected volatility.  The new process does look better to me, but I’ve been surprised that the new VIX and the old VIX (listed as VIXMO) sometimes differ by as much as plus/minus 10 percent.

Disagreements between the two indexes are not due to only one factor, but clearly one improvement was to eliminate the week of the month where the VIX was calculated using extrapolation.

The VIX provides a 30 day estimate of volatility, but the S&P 500 options (SPX) used in the VIX calculation have fixed expiration dates.  The CBOE transforms the options’ data into the VIX by using volatility specific interpolation / extrapolation.  For example, if you have a volatility number for options that expire in 10 days and another for options that expire in 38 days you can reasonably assume that the VIX level should be between those two numbers.

One requirement with the old VIX calculation was that it couldn’t use options with less than 7 days to expire.  When the 7 day restriction was reached the calculation switched to using options that had more than 30 and 58 days until expiration.  The chart below shows the calculation right after that switch on January 12th, 2015.


The blue and red bars are the volatility numbers (VINMO & VIFMO) from the S&P options and the green bar is the VIX calculation extrapolated from those two numbers.  For details on that process see: Calculating the VIX Index—the Easy part

Normally this extrapolation was reasonable, but if the market is nervous the shorter term volatility values climb.  January 12th, 2015 was a case in point—notice how the light blue VXST bar (9 day volatility) is higher than the VIX estimate.

The next chart shows the new and old VIX calculations together.  The black dotted line shows the interpolation used for the new VIX calculation; the blue dotted line shows the old VIX extrapolation. The black vertical bar shows the VIX estimate.

VIX cacl-graph

Clearly the two calculations have a major difference of opinion —the new calculation’s result is 7.5% higher (19.60 vs. 18.15).

The CBOE’s new calculation always uses options that expire within a week of the VIX’s 30 days.  The red and orange triangles show their values on January 12th.

The old VIX calculation misses the fact that the shorter term volatility has ramped up.

The CBOE provides VIX style calculations on six different sets of options used in their VIX, VIXMO, and VXST calculations.  These calculations don’t need time extrapolations / interpolations so that source of potential errors is eliminated.   The chart below shows how they mapped out on January 12th, 2015 (click image to enlarge).

vix term c+m

The green dots on the top line represent the CBOE VIX style volatilities over time.  The vertical black bar shows the old VIX calculation and the purple outline above it shows the new VIX calculation.

In this case the new VIX calculation is more accurate, cleanly mapping into the overall volatility term structure.


Additional Resources:

Prediction: Dec 31, 2015 S&P 500 close at 2346 up 13.9%

Thursday, January 1st, 2015 | Vance Harwood

My 2015 year end prediction is based on the trend channel shown below, which has been in place since around May 2012.


There’s nothing magical about this channel. The market will transition from it at some point, and I think it’s important to plan for that, but for the moment the channel is the trend.

This sort of trend channel has characterized the last three bull markets.

SPX channels 1995

The blue line in the chart is the 250 day simple moving average.

I suspect these patterns originate from random market moves—which often look like trend channels— interacting with human / computerized pattern matchers that transform random patterns into a self-fulfilling prophecies.  When the market starts approaching the top of the channel followers start selling, and they buy when the low channel is breached—reinforcing the pattern.

Anyone using that approach would have done very well the last two years.

As bull markets move into the territory of bubbles and nose-bleed valuations the risk of the trend ending increases, but predicting the end is notoriously difficult.  You can be years early in calling the top.  In Jack Schwinger’s excellent book “Hedge Fund Market Wizards”, he comments, “Predicting the top of a bubble is like trying to predict the weather a year out.”  In the book hedge fund manager Colm O’Shea agrees, but adds, “But you can notice when things have changed.”

Colm relates how in 2006 and 2007, “I was thinking the markets were in a completely unsustainable bubble.”, but rather than try to pick the top his firm stayed long.  “We were quite happy to be part of the bubble.”  However they did limit their risk by doing trades with limited downside (e.g., buying options rather than the securities themselves), and they waited for things to change.  When they did notice a big change (LIBOR rates spiking in August 2007) they moved to bearish positions.

In the chart above, the last two bull markets signaled they were really over when the index was below the channel and below the 250 day moving average for more than a couple days.  I will certainly be watching those metrics during 2015.

I will also be matching the health of the overall US economy, because fundamentally the market relates to the economy.  The next recession and the next bear market will be linked together.  Some of the factors I will be watching:

Interest rates

  • The Fed has signaled that it may start raising interest rates in 2015. While the market might falter when this happens, I think the biggest issue will be the inflation rate behavior compared to the Fed’s 2% target.  Some feel that the Fed’s actions in expanding the money supply created a powder keg that will explode once inflation starts rising.   Others worry that increasing rates will undermine the recovery, risking sliding back into deflation and recession.   I favor the latter because the Monetarists who think only the money supply matters regarding inflation have been completely wrong the last 5 years.

Oil prices

  • The dramatic drop in oil prices has something for everyone. Commuters and airlines loving it, drilling equipment manufacturers hating it, oil tanker business loving it, holders of junk grade debt from energy companies hating it, and so on.   Overall I think these impacts will mostly cancel out and since the energy segment of the economy was overheated I think some scaling back will be healthy.

Wage Growth

  • The majority of USA workers have seen their wages barely increase over the last decade while corporate profits have increased dramatically. Unless power shifts back to labor, unlikely I think, we won’t see general wages increases much over the rate of inflation.

Stock Buybacks

  • In the last four quarters S&P 500 companies spent $567 billion buying back their own shares—a year to year increase of 27%. While it pains me that companies apparently don’t think that they can find a better place to invest this money, I understand that preventing share dilution from stock options / restricted stock issuance makes sense (although most of these shares go to already highly compensated employees).  What I abhor is companies (like IBM) going into debt to finance stock buybacks in an attempt to hide a deteriorating business.  This behavior has bubble possibilities because the next recession will knock out these companies and those that hold this toxic debt.


  • The European austerity policies, rather than solving problems have extended its recession and exacerbated unemployment. The Eurozone poses no danger of overheating the global economy.   As the US economy grows the dollar will continue to climb—providing a natural braking mechanism as imports get cheaper and exports relatively more expensive to trading partners.

In the year or two before the tech crash of 2000 and the financial crisis of 2008 the market felt overheated to me.  Before those crashes there was an outrageously overvalued tech sector, and a vastly overheated home building / mortgage industry respectively.  So far I don’t see the next bubble forming.   Yes, trillion dollar student loan debt is worrisome, but I don’t see it crashing the economy.  Yes, oil prices dropping 50%+ will put the pinch on oil business, but again I don’t see the domino effect that goes with the collapse of a bubble.  To destroy the momentum of a growing economy requires a collapse on multiple fronts—no single facet has enough impact.

So, for the short term—at least for a week or two—the trend channel is safe.

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