Of all the issues discussed in this space, undoubtedly the one that captures the imagination of most readers is the subject of VIX-based exchange-traded products. I get more questions about the construction of these products, how they respond to the VIX futures term structure, what factors influence performance, etc.
For these reasons I thought it might be instructive to update my VIX ETP landscape chart and include performance data from the September 14th market closing high of SPX 1465 to today’s close of SPX 1377. During that period, the SPX declined 6.0% on a close-to-close basis, while the VIX jumped 27.4% during the same period.
So how did the VIX ETPs fare while the market was selling off?
In examining the graphic below, the first thing you probably notice is that only 5 of the 19 VIX ETPs were able to manage gains during the selloff. In fact the average (mean) VIX ETP performance was a disappointing -4.9%, while the median return was -6.7%. Even more interesting, the inverse volatility products actually outperformed their long volatility counterparts and had the top performer of all, the VelocityShares Daily Inverse VIX Medium-Term ETN (ZIV).
Guest post by Vix and more.
Investors who have been trading the VIX futures, VIX options and VIX exchange-traded products in 2012 have no doubt observed that there has been a wide gulf between the volatility predicted by the VIX front month futures and the back month futures. How wide? Well the graphic below shows the average (mean) normalized term structure for each year since the VIX futures were launched, back in 2004. In normalizing the data, I have set the average front month VIX futures contract to 100 and have expressed the averages of the second through seven months as multiples of the front month.
[Note that while the VIX futures were launched in 2004, consecutive VIX futures contracts for the first six months were not available until October 2006, hence the dotted lines for these years to reflect the erratic nature of the data. Also, I have included the seventh month contract in the calculations because this month is critical to the calculations of a number of VIX ETPs, including VXZ, VIXM, ZIV, etc.]
What about that “extreme” reading of VIX term structure. Bill Luby of Vix and more starts the explanation process.
Before I dive into a series of posts about the VIX futures, I think it is important to add some context in the form of several observations about the relationship between the VIX and the historical volatility (HV) of the S&P 500 index. In the absence of any information about the future, it turns out that historical volatility (a.k.a. realized volatility or statistical volatility) can provide a reasonably accurate measure of future volatility. In fact, it is more difficult than one might imagine to incorporate information about the future to come up with a better estimate of future volatility than what can be gleaned just by extrapolating from recent realized volatility.
Looking at historical data, the VIX has an established history of overestimating future realized volatility. In fact, in the 23 years of VIX historical data, there was only one year – 2008 – in which realized volatility turned out to be higher than that which was predicted by the VIX.
As the chart below shows, early traders made a habit of dramatically overestimating future volatility. From 1990-1996, for instance, the VIX overshot realized volatility by an average of 49%. Since 1997, the magnitude of that overshoot has dropped dramatically, to about 24%, as investors apparently began to realize that they had been overpaying for portfolio protection in particular and for options in general.
Imagine the world economy as an armada of ships passing through a narrow and dangerous strait leading to the sea of prosperity. Navigating the channel is treacherous for to err too far to one side and your ship plunges off the waterfall of deflation but too close to the other and it burns in the hellfire of inflation. The global fleet is tethered by chains of trade and investment so if one ship veers perilously off course it pulls the others with it. Our only salvation is to hoist our economic sails and harness the winds of innovation and productivity. It is said that de-leveraging is a perilous journey and beneath these dark waters are many a sunken economy of lore. Print too little money and we cascade off the waterfall like the Great Depression of the 1930s… print too much and we burn like the Weimar Republic Germany in the 1920s… fail to harness the trade winds and we sink like Japan in the 1990s. On cold nights when the moon is full you can watch these ghost ships making their journey back to hell… they appear to warn us that our resolution to avoid one fate may damn us to the other.
Volatility at World’s End symbolizes a new paradigm for pricing risk that emerged after the 2008 financial crash and is related to our collective fear of deflation. The metaphor encapsulates the unyielding sense of dread that the global economy will plunge into the dark abyss and is the source of major changes in volatility markets. Today the existential fear of world’s end deflation is so powerful investors are willing to pay the highest prices for portfolio insurance in nearly two decades. The market for forward volatility has become unhinged as the SPX variance and VIX futures curves sustain historically high premiums over low spot vol. My argument is not that this extreme fear is misplaced but that it is mispriced. Like Odysseus in the epic poem the global economy is trapped between the monsters of Scylla and Charybdis. We risk one to avoid the other. From one world’s end to the next sometimes I wonder if decades from now we will look back with the hindsight that we were all hedging the wrong tail.
Guest post by Bill Luby of Vix and more.
For a variety of reasons, investors seem unwilling to embrace the current rally and with each day the market rises, I see a scramble in the indicator forest to find some sort of proof that stocks are finally, inevitably going to correct…and soon. I need to give this phenomenon a name, so I am going to call it indicator hunting and define it as a companion to confirmation bias.
I discussed this subject a little over a month ago in What the VIX Kitchen Sink Chart Says (it hasn’t said much lately, but I’m trying to teach it sign language), when I noted:
“One of the more interesting developments of 2012 has been to watch the diminution of the strident bearish narrative that has been focused largely on the collision course between a preponderance of debt and low or negative growth. The bullish beginning to 2012, however, has not prompted many in the way of converts to the bullish camp. Instead, there have been whispers of ‘…overbought…’ that have turned into a soft murmur and are now verging on becoming loud chorus. Suddenly the general consensus seems to be that stocks just do not deserve their current lofty valuation.
In this type of environment, many investors become particularly susceptible to confirmation bias and scramble to find one or more indicators which will tell them what they have already begun to believe: that a major correction is likely just around the corner.”
Many pundits talk about volatility, Vix, fear etc without even having the slightest idea of what volatility is. Others explain complex matters in a complex way, so “ordinary” people don’t understand what these quants actually talk about. One of the brightest minds when it comes to volatility and good reports on volatility, is Marko Kolanovic of JPM. Below some thoughts on volatility for 2012, courtesy Mr Kalonovic.
In 2011 we witnessed two distinct market regimes: very low volatility in H1, and extreme correlation, poor liquidity and high volatility in H2. Escalation of European sovereign credit crisis in August caught investors by surprise, triggering a series of large risk on/off flows. The record drop in equity liquidity and the rise of cross-asset correlations effectively shut off equity markets for fundamental stock investors. In addition, derivative hedging flows at times overwhelmed liquidity, further adding to market volatility and correlation.