VQTS: A Large Cap Investment That Protects Itself

Thursday, July 16th, 2015 | Vance Harwood

In my opinion VQTS is the best exchange traded product for solving the essential conundrum of the stock market: how to run with the bulls without getting mauled by the bears.

The algorithms in VQTS are tuned to outperform the other hybrid volatility funds like Barclays’ VQT and VelocityShares’ SPXH during good times and to be competitive during the bad times.

We don’t have much trade data since UBS only introduced VQTS on December 3rd, 2014.  It stumbled in its first month of trading, but then recovered during the first half of 2015—but after 8 months it is only lagging SPX by 0.5% since its inception.

Hybrid-since-VQTS incept


All of the hybrid volatility funds dynamically allocate assets into the S&P 500 (SPX), VIX futures, and cash depending on market conditions.  VQTS is the first fund of this type that invests all of its assets into the S&P 500 when the market’s overall volatility is low.  This avoids the costs of hedging when the market is least likely to go down—during the long upward stretches of bull markets.  In comparison, two similar funds, Barclays’ VQT and PowerShares’ PHDG both have at least 2.5% of their assets allocated to long volatility—and that small amount significantly drags down their returns during bull markets.

The chart below compares the simulated performance of VQTS compared to SPX, VQT, and SPXH from early 2006.



VQTS defines low volatility as being historical volatility less than 10% using the higher of two exponentially weighted moving averages on volatility.  Before shifting allocations VQTS requires that its historical volatility measure move by more than 10% from the target volatility used at its last rebalancing.  Once the target volatility climbs above 10% VQTS starts holding cash and volatility securities (2/3rds cash, 1/3rd volatility) in addition to the large cap S&P 500.  The table below shows the range of asset allocations as realized volatility increases.


VQTS Asset Allocations

Realized Volatility
(exponentially weighted)
Equity % Volatility % Cash %
0% to 10% 100% 0% 0%
10% to 20% 100% to 50% 0% to 16.7% 0% to 33.3%
20% to 30% 50% to 33.33% 16.7% to 22.22% 33.3% to 44.44%
30% to 40% 33.33% to 25% 22.22% to 25% 44.44% to 50%
40% to 50% 25% to 20% 25% to 26.67% 50% to 53.33%
50% to 60% 20% to 16.67% 26.67% to 27.78% 53.33% to 55.56%
60% to 70% 16.67% to 14.29% 27.78% to 28.57% 55.56% to 57.14%
70% to 80% 14.29% to 12.5% 28.57% to 29.17% 57.14% to 58.33%
80% to 90% 12.5% to 11.11% 29.17% to 29.63% 58.33% to 59.26%

In October 2008 the realized volatility as computed by VQTS’ algorithms peaked at 82%


When not fully allocated to equities VQTS takes a long or short position in VIX futures depending on the curvature of the futures’ term structure.  The term structure is the curve that’s formed if you plot VIX futures’ price vs time to expiration.  The decision to go long or short is determined by the comparison between the slope of the two nearest to expiration futures (1st and 2nd) and the slope of the 4th and 7th month futures.  I’ve marked up the chart below from vixcentral.com to illustrate the calculation.



VQTS’ curvature calculation is similar, but not identical to the more familiar designations of contango and backwardation for futures’ term structures.  In general VQTS will go long volatility if the term structure is in backwardation (futures prices less than spot), and short volatility if the curve is in contango.  This approach would have worked well in the past, profiting from the fast rise of volatility as a crash / big correction develops, and then switching to be short volatility as volatility mean reverts.  The chart below shows the simulated performance of VQTS during the 2008/2009 crash.


VQTS experienced around a 20% drawdown in the fall of 2008 before rallying to a year end gain of +13%.

Many strategies that backtest well on historical data do not perform well once they go live, but as I noted at the beginning of this post VQTS has already shown that it can approximate the S&P 500 during periods of low volatility—the condition the market is in 75% of the time.  VQTS’ drawdowns during crashes and corrections are likely to be significant, but VQTS’ strategy of going long volatility during panicky periods and short volatility during the recovery should continue to work well as a way to power through downturns.

UBS did think about Black Swan events when constructing this fund.  If VQTS was allocated to short volatility when a major disaster (e.g., terrorist attack) occurred the fund could experience very heavy losses.  If VQTS is down 60% or more intra-day from the previous close or the indicative value drops below $5 the fund is terminated.  This is called an acceleration.  The shareholder receives a payout that is equal to the liquidated assets of the fund—which may be higher or lower than the acceleration threshold levels.

VQTS is still a small fund with only $25 million in assets, so investors are hesitant to invest in it, but since the S&P 500 and VIX futures are its underlying securities its liquidity is excellent.  Bid/ask spreads have been reasonable—in the 6 to 7 cent range (0.3%).  Over time I expect its assets to grow into the $500 million range of its closest competitors, VQT and PHDG.

Everyone knows this bull market will end, the tough part is guessing when. With VQTS you can ride the bull and be prepared for the inevitable bad ending.

Under the Hood of VQT—Looking Forward to a Crash

Friday, April 17th, 2015 | Vance Harwood

An ideal volatility investment would hold its value during quiet times and then ride volatility up as the market panics.  Barclays’ VQT is one of the two Exchange Traded Products (ETPs) that Barclays has designed to try and fill this need (the other is XVZ).

I created a spreadsheet to simulate VQT’s allocation methodology (click here for more information) and then backtested the fund’s performance back to March of 2004—the beginnings of VIX futures trading.  The results are shown below, compared to an equivalent investment in the S&P 500.

$1K in VQT vs SPX


Impressive.  Of course, past performance is no guarantee of future success—UBS’s XVIX is an example of a volatility fund that backtested great, but has gone nowhere since introduction.

VQT reacts to market dynamics by shifting its allocations as often as daily between the S&P 500, a VIX futures position (essentially VXX without the fees), and cash.  There are five S&P 500 / Volatility settings:

S&P 500 Volatility Market Condition
97.5% 2.5% Quiet
90% 10%
85% 15%
75% 25%
60% 40% Very Volatile


VQT also has a panic room.  If the fund drops 2% or more in the last 5 business days it triggers a stop loss that shifts everything to cash for up to 5 days.

By monitoring the S&P 500’s volatility and trends in the CBOE’s VIX index VQT’s algorithms determine which of the 5 non-panic settings to use.  The S&P 500’s historical volatility for the last month is the big knob, and then volatility trends are used to tweak the settings up or down one.  The realized volatility breakpoints are 10%, 20%, 35%, and 45%.  The chart below shows the S&P 500 volatility compared to these trigger points since 2004.  The SPX itself is shown also; its scale is on the right.

SPX Historic volatility compared to VQT triggers plus SPX

The volatility trend metric that VQT uses monitors the 5 and 20 day moving averages for VIX.  If the short term average is higher than the longer term average for ten days the trend is judged to be up (+1), and if the long term is higher than the short term the trend is down (-1).  Otherwise the trend variable is set to zero.   The chart below shows the volatility trend indicator compared to VIX during an “interesting” period that includes the 2008/2009 meltdown and the Flash Crash.

VQT volatility trends vs. VIX

The implied volatility trend is essentially a 3 state version of the VIX index—up, down, or sideways…

The matrix below, taken from Barclays’ prospectus, shows VQT’s non-cash settings determined by S&P 500 realized volatility and VIX trends are shown below.

In addition to these settings there is the 100% cash stop loss allocation of VQT, which occurred a surprising 156 times in the eight year span I evaluated—7.5% of the time.   The chart below shows that this shift into cash, while most prevalent during the 2008/2009 crash, can occur frequently in both bull and bear markets.

VQT, SPX/20, and VQT stop loss occurrence

Intuitively there are two scenarios where VQT could fall more than 2%:

  1. The S&P 500 is falling and the VXX allocation is not big enough or not gaining enough to offset the drop in equities
  2. Losses in the VXX position pull down the overall value of the fund

My simulation shows the VQT stop loss being triggered 108 days, 2/3rds of the total number, when the S&P 500 was dropping and the volatility trend was flat or increasing—so scenario #1 is the most common.

The stop loss feature makes VQT the best of the hybrid strategy ETNs in reacting to fast volatility spikes.  The equity/volatility allocation knobs are tied to SPX and VIX moving averages are inherently slow to react, but the stop loss feature triggers quickly, moving the fund into cash after a single down day of 2% or more.  VQT won’t benefit from the initial spike, but the pause buys time for the allocations to adjust to new market conditions.

Since its inception August 31, 2010 VQT has performed well in an overall bullish market.   It’s roughly tied with S&P 500 with growth rates of 28% vs. 30%, but it sports a maximum drawdown of only 6% vs. 18% for the S&P 500.   In the July/August 2011 market correction, when the S&P 500 lost 13%, VQT was up 5%—an impressive performance.

It’s odd when holding a primarily long equity position to hope for a market crash, but with VQT a market panic is not something to be feared.

Historical Backtest on VQT

Tuesday, October 14th, 2014 | Vance Harwood

I have backtested Barclays’ VQT ETN back to when VIX volatility futures first started to trade in March 2004.  I have made two versions of the spreadsheet available for purchase below.  One with results data only and the other version with formulas and required indexes included.  I have included the simulated daily closing values with  the 0.95% annual fee from March 29, 2004 until July 5th, 2012.  The results of the simulated values compared to actual values are shown in the chart below.  My results match samples from the  published SPVQDTR underlying index within 0.35%.

Simulated VQT vs Actuals

VQT looks like a very good way to have exposure to the general market and profit from major market panics.   For details on VQT see:

For more information on the spreadsheets I have for sale see this readme.

If you purchase the spreadsheet  you will be eventually be directed to paypal where you can pay via your paypal account or a credit card. When you successfully complete the paypal portion you will be shown a Return to Six Figure Investing link.    Click on this link to reach the page where can download the spreadsheet.  Please email me at vh2solutions@gmail.com if you have problems, questions, or requests.


A Covered Call That’s Long Volatility

Friday, January 11th, 2013 | Vance Harwood

Covered calls are an example of  positions that are short volatility.  I hadn’t thought of it that way until Sheldon Natenburg, the author of Option Volatility & Pricing  pointed that out in a fascinating interview in Expiring Monthly  (http://tinyurl.com/6wwplf9).   A covered call position is profitable if the underlying equity stays the same or goes up, but in a big market downswing, when volatility spikes up,  the modest potential profits from a covered call are more than wiped out by the losses in the underlying.

Unfortunately it is usually expensive to hedge a short volatility position.  The two most common strategies have problems:  VXX typically has roll yield losses, and VIX/VXX options have significant time decay.  Recently I started looking at Barclays’ VQT ETN, a fund that is intended to be long volatility.  The chart below compares $1000 invested in SPY and VQT starting in September 3rd, 2010—VQT inception date.

$1k investment in SPY and VQT

In bull market phases VQT underperformed the S&P 500  by about 50%,  but during the -19.5%  drawdown in August 2011 VQT only dropped 3% before going on a short term volatility fueled binge that lifted it 20%.    The next chart shows the day-to-day percentage moves of VQT vs SPY since June 2011.

Daily percentage moves SPY vs VQT

When times are volatile, VQT shifts its investments to include more short term volatility—which lowers its correlation to the S&P 500 to about 50% or 60%.  In very quiet times, like the end of December/January VQT shifts to a almost pure S&P play—giving it the nearly 100% correlation you see at the right side of the chart.   The next chart is from the VQT prospectus, showing the backtested, theoretical performance of VQT since 2005

VQT vs S&P500 backtest to 2005

VQT looks almost tailor-made for covered call writing.  Its low drawdown behavior limits capital risk while its volatility is similar to the S&P 500.  Unfortunately there are no options available on VQT, so we’ll have to get creative in developing a covered call style position.  Since much of VQT’s composition is direct exposure to the S&P 500 I will use SPY options as logical building blocks.  A covered call is a short call position hedged with a long equity position.    Since brokers won’t accept a long VQT position as a hedge for a short SPY call and I don’t want to have naked calls, I’ll protect my short call position with long out-of-the-money calls—creating a call spread.     I’m not too concerned about losses on these credit spreads, because VQT is a natural hedge for the position, so I’m comfortable with a $2 spread in the option strike prices.

Profitability analysis:

Market Action VQT action SPY call credit spread action Overall Profit
S&P 500 strongly up Up, but not as much as S&P Worst case loss.  Loss is premium received at creation minus $2/ option pair Neutral to small loss
S&P 500 up Up, but not as much as S&P  Neutral to profitable, with profit equal to premium received at creation minus any in-the-money intrinsic value. Modest profit
S&P 500 down Down, but not as much as S&P  Profitable, keep full premium received at creation Neutral to small loss
S&P 500 strongly down Strongly up as volatility portion kicks in  Profitable, keep full premium received at creation Very Profitable


The spreadsheet that provides the VQT backtest data from March 2004, including all formulas is available here.


The Volatility Landscape

Sunday, October 12th, 2014 | Vance Harwood

VIX + VIX Future Term Structure May 2011- March 2012


  • CBOE
    • The CBOE plans to extend VIX® Futures trading by over 5 hours—aligning with the London Stock Exchange open, and adding a 45 minute post settlement trading period 4:30 ET to 5:15 ET Monday through Thursday.
    • Two new volatility indexes, DLVIX and DSVIX are documented on the CBOE website.   These indexes were developed in cooperation with the French bank Société Générale and are now being used with two new European ETFs.   A quick look suggests these indexes switch VIX futures allocations based on term structure and VIX momentum.
    • Volume in VIX Futures continues to surge to record highs with April’s volume climbing 26% higher than March.  The year to year volume growth was 141%.
  • VIX Central improved its historical VIX Futures term structure graphs by switching the time axis from contract months to time to expiration.   This change greatly reduces the chances of misinterpreting term structure differences across contract expiration boundaries.  See this post for more information.
  • For the first time ever an inverse volatility fund—VelocityShares’ inverse short term volatility ETN XIV has taken second place in overall volatility fund assets under management (AUM) with $440 million.  The leader, Barclays VXX has $1.15 billion.  Third place goes to ProShares’ UVXY 2X short term volatility ETF with $344 million.  For more on inverse volatility see this post.
  • Yahoo finance now reports Exchange Traded Product’s (ETP) AUM as net assets in their standard quote information and has made some other information available (e.g. shares outstanding, total cash) with special tickers.   The topics and example tickers shown below for SPDR’s JNK:
    • Intraday Indicative Value   ^JNK-IV
    • Shares Outstanding   ^JNK-SO
    • Net Asset Value ^JNK-NV
    • Estimated Cash ^JNK-EU
    • Total Cash  ^JNK-TC
  • I recently found out about the Quandl data resource—a free source of downloadable price data  futures, stocks, rates, currencies, commodities; macro-economic data from FRED, BEA, DOE, Census, USDA, WB, UN, OECD; demographic and society data; and corporate financials.  There’s a lot of good stuff there.



  • With both UVXY and TVIX trading well below $10 per share the question of upcoming reverse splits has returned.
    • I expect ProShares to reverse split UVXY 10:1 in May or June—they don’t want to lose the momentum that they have built up.  (announced 10:1 split 25-May, effective June 10 link)
    • The last time around (December 2012) Credit Suisse waited until TVIX has dropped below $1 per share before doing a reverse split.  With $188 million in assets, I doubt they will just let this product fade into oblivion, but given their track record of procrastination I’m guessing we won’t see a reverse split until TVIX is south of $1—maybe in October / November.


White Papers

  • Easy Volatility Investing” by Tony Cooper
    • This paper took 2nd place in the National Association of Active Investment managers’ (NAIIM) recent Wagner Award white paper contest.   It provides a good overview of volatility trading and then does a thorough evaluation of 5 different trading strategies for volatility products: buy & hold, momentum, roll yield, volatility risk premium, and hedged.
  • Option traders use (very) sophisticated heuristics, never the Black-Scholes-Merton formula”   Haug & Taleb
    • I hadn’t seen this 2009 paper until recently.  The authors claim that the practical impact of the Nobel Prize winning work of Black-Scholes-Merton on the options markets is significantly over emphasized.  They argue that structural relationships like put / call parity and compatibility between options combinations at various strikes (e.g., no negative butterflies) are the true forces setting options prices.
  • Volatility Trading: Trading Volatility, Correlation, Term Structure and Skew” Bennett & Gil
    •  Over 200 pages of wide ranging information—from covered calls to exotic options, to links between CDS spreads and implied volatility.  Something for everyone.



  • I’ve added Citi Group’s CVOL and Barclays’ XVZ to my “Not recommended” list of volatility funds.
    • CVOL’s assets under management have dropped to $2.2 million and its bid/asked spreads are very wide.  Its strategy of trying to track volatility is sound, and their contango losses are less than UVXY or TVIX, but it’s just too small.
    • The intent of Barclays’ XVZ was to create a fund that was long volatility, but could be held during quiet times without losing much if any money.  XVZ attempted to do this by hedging a position in medium term volatility products with a short position in short term volatility.  Unfortunately for XVZ, the VIX Future term structure shifted about the time the fund was introduced in such a way that the hedging didn’t work and it has lost 30% in the last year.  XVZ might do OK during times of high volatility, but until it establishes some sort of track record in that environment I’d recommend staying away.   For more on XVZ there’s a good article “The Hedge That Wasn’t” posted by Season Investments.


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