True knowledge is not what you know but certainty in what you do not. Volatility is simply about putting a price on that. Drawing from the famous quote by Donald Rumsfeld, former US Secretary of Defense(20), the trader of volatility must be able to identify “known unknowns” and “unknown unknowns” while simultaneously making a market in both. Modern volatility markets know that the global economy is facing deflation... but they also know that global central banks will be right there to respond to any crisis. The single most important “unknown unknown” today is any random event that may unexpectedly cause global central banks to withdraw their stated support of markets.
Moral hazard has contributed to a significant build up in short and leveraged volatility creating a shadow ‘volatility gamma’ that reinforces the current trend in volatility direction. Rising volatility is followed by more rising volatility and vice versa. Volatility is crushed whenever a central bank responds to crisis and thereafter leverage is re-applied in even greater amounts in a cycle of moral hazard. The pattern is creating a pro-cyclical monster of short volatility that, if left unchecked will contribute to a repeat of the May 2010 Flash Crash or 1987 Black Monday Crash. August 2015 was just an appetizer.
In 2012 Artemis coined the term “Bull Market in Fear” to explain a regime of volatility defined by investor's willingness to pay almost anything to shield their portfolios from the next deflationary crash. Between 2013 and October 2014 we experienced a “Bear Market in Fear” defined by a rising short volatility complex and low risk premiums for selling variance. Ever since last fall, we have entered into one last dangerous phase in the volatility cycle. Forward volatility markets no longer fade volatility out of denial; they fade volatility out of the prospect of central bank support.
This is a new era of hyper-moral hazard whereby a central bank reaction function is fully priced into option markets. Volatility markets do not believe central banks will let us fail.
For evidence, consider that the VIX futures markets faded the August VIX spike by the greatest margin in history. The graph below shows the ratio of the VIX to the market’s one-month forward expectation of the VIX. The higher the ratio the greater the market’s confidence in volatility mean reversion. August 2015 dwarfed all other crises in mean reversion expectation including October 2008, May 2010, and August 2011. The entire VIX market was essentially one large leveraged bet that central banks would respond to the crisis… and it paid off! What if it didn’t?
The VIX is experiencing epileptic seizures including erratic and violent outbursts up and down at the most frequent pace in history as new sources of structural short convexity interact with interventionist policy responses to crisis. The VIX has registered a quantifiable ‘supernormal’ (five standard deviation +) move up or down every three months over the last two years.
In July-August 2015 alone, we experienced the single largest multi-day drawup and drawdown in the history of the VIX index. Artemis ranks consecutive drawups and drawdowns (trough-to-peak or peak-to-trough) in volatility and models them as a power law distribution. The distributions of a wide variety of physical, biological, and human phenomena closely follow this form. Examples include earthquakes, deaths in war and terrorism, populations of cities, solar flares, word frequencies in language, movie box office receipts, and asset price movements. When you logarithmically rank the event magnitude of these natural and human phenomena the majority of observations will align linearly along the x-axis as a power-law function (see white line below). Violations of the power-law function are supernormal events because their results contain a degree of reflexivity that exceeds the exponential growth function. Examples of supernormal violations in power laws across other phenomena include death counts in WWII ranked among all wars, box office receipts of the movie Titanic, the Titanic disaster itself, the 9.2 Magnitude 1960 Chilean Earthquake, the population of Tokyo, the 1987 Black Monday Crash, and the 9/11 terror attack in NYC. Three of the top ten supernormal VIX increases and four of the top eight supernormal VIX decreases have occurred in the last year alone! The top eight ranked drawdown collapses in VIX have all occurred during the post-2012 monetary regime. Power-law violations in VIX to the downside and upside are now happening with regularity!
Volatility markets are demonstrating deep uncertainty in the very nature of uncertainty itself. The schizophrenic behavior of volatility is a deep warning sign for policy makers that something is not right. Implied Volatility-of-the VIX (“CBOE VVIX”) reached the highest levels in history on August 24th, 2015. The volatility-of-VIX rose higher than levels achieved even during the 2008 financial crisis, 2010 Flash Crash, and 2011-debt downgrade crisis.
Many will point to structural considerations as a driver including the proliferation of VIX exchange traded products and the new spot-VIX calculation methodology. While these are important factors, they are only part of the story.
To understand why the volatility of volatility reached new highs we have to engage in deep meta-thinking about our reaction to change. Volatility provides exposure to our collective insecurity towards an unknowable future. Likewise, to short volatility is to express personal confidence in the status quo of market affairs despite a broader fear of change. To go long volatility is to express fear that change is coming.
Volatility-of-volatility is simply the war between these two different modes of perception... shifting perceptions in the nature of uncertainty itself. If uncertainty is rising so should the VIX... but there is a very different type of uncertainty to evaluate … the uncertainty that central banks will intervene. When global central banks seek to defend the status quo and mean reversion it becomes increasingly difficult to accurately gauge the probability of change in markets. Volatility markets are now gaming central banks in addition to fundamental economic and technical conditions. If we are unclear from one moment to the next whether radical change or the status quo will prevail than volatility-of-volatility should logically rise.
Volatility mean reversion has been an abnormally profitable bet during the regime of pre-emptive strikes on financial risk. Following each tail event in volatility, we are experiencing another tail event in the magnitude of volatility declines. Central banks refuse to let volatility remain elevated and are quick to react to any crisis.
Between August and September 2015 the VIX collapsed faster than ever before following a spike to 40 (see red line below) due to another massive stimulus response by central banks. China cuts rates, devalued the Yuan, and purchased an estimated $263bn of equity (9.2% of freely traded shares) to artificially prop-up their stock market before a nationalistic military parade. Following China, the ECB expanded their QE program. The graph below demonstrates the historic decline in volatility by showing the average, high, and low trajectory paths of the VIX the ensuing fifteen days following every implied volatility spike to 40.
Likewise, the area chart below graphs the forward probability distribution of S&P 100 implied volatility (VXO) following a breach of the 35 barrier in spot-vol.
As expected, implied volatility exhibits an exceptionally positively skewed distribution following a ‘risk-off’ event, but notice how the current trajectory of VXO lies on the far left of the distribution. Central banks refuse to let volatility remain elevated but this is creating a new set of shadow risks...Global central banking has artificially incentivized bets on mean reversion.