Being long (NYSEARCA:UVXY) - either as a hedge or as a speculative position - hasn't been to lucrative of late. The 2X VIX ETF has lost 75% of its value since the first of the year.
As stocks exploded off the 1560 lows on June 24th it certainly made sense that UVXY would settle back down a little but as the chart below shows UVXY didn't just settle back a little - it crashed. Here's a look at UVXY since the first of the year:
Here is the S&P 500 (NYSEARCA:SPY), VIX and UVXY over the last month:
UVXY as a 2X ETF did a pretty good job of meeting the ETFs defined goal of 2 times the VIX. VIX was down roughly 25% since the June low and UVXY was down roughly twice that amount.
This next chart is the real point though and reflects that significant money has been flowing into UVXY:
As of June 25th the number of shares outstanding in UVXY was 2,389,000 and as of July 25th that number had increased to an all time high of 7,889,000. That is more than 3 times the June 25th low in total shares outstanding and suggests a lot of short term hedge protection is being taken that is not reflected in the VIX itself.
Here is the short side of the UVXY trade - (NYSEARCA:SVXY) - showing significant outflows:
There are a couple of significant points to be made here. The first point is that the number of instruments one can use to implement hedges in equity positions today compared to times past may be part of the reason why VIX itself isn't pricing in much fear. In other words investors and traders are using instruments like UVXY in lieu of S&P 500 puts to take downside protection.
The second point is that by using alternate instruments in lieu of the more traditional S&P 500 puts and calls traders and investors are not moving VIX much as VIX is a function of the put/call ratio of the S&P 500. Kind of ironic in a way in that those who are seeing high risk in the market are using ETFs that reflect VIX and in so doing VIX itself may no longer reflect market anxiety.
Here is a look at a chart showing the distribution of puts and calls on SPX for August:
Even more useful as a basis of comparison is a look at the cumulative total of puts and calls at all strikes between 1200 and 1900:
One can see from the chart above that the overall total of puts and calls for the August expiration are well balanced - thus a relatively low VIX value. Just looking at the total number of puts at all strikes between the referenced range is also informative. The total is 9,858. Since each put represents 100 shares the numbers of shares reflected by the puts for the August expiration total 985,800. Compare that to UVXY shares outstanding of 7,899,000 and it seems logical to conclude that VIX indeed may not be reflecting realistic market fear levels.
In other words traders and investors appear to be using the VIX ETFs in lieu of actual SPX puts and calls to hedge risk. It can be reasoned then that VIX is less relevant today than before the inception of the VIX ETFs. However, since the ETFs are priced based on the VIX futures and the VIX futures are priced based on VIX itself the use of the ETFs to hedge risk actually works to reduce volatility risk. Let me explain further.
Over the last several months I have set forth the thesis that primary dealer banks - acting as market makers - are attempting to manipulate price and prevent a stock market crash scenario from developing. That of course is supposition and based on what I see as compelling empirical support that indicates the markets are bought most aggressively when macro events suggest the market should be sold aggressively. I am not willing to reject that theory but do want to suggest another possibility for consideration.
Specifically, we know the algos factor in volatility as measured by VIX and VIX isn't reflecting much in the way of volatility. Friday's close on VIX was 12.72 and that implies a 3.67% shift up or down from current price. In other words, just using VIX as a basis for forecasting a 30 day trading range based on Friday's close that range would be between 1628 and 1753.
A more logical approach to calculating the 30 day range is to look at volatility as reflected by VIX applied to the 50 day moving average. Here is a look at the S&P with the 50 day moving average plotted along with the 2 standard deviation Bollinger bands:
Confirmation is always comforting and by coincidence the range using the implied high and low based on a VIX close of 12.72 correlates almost perfectly to the plus and minus 2 standard deviation Bollinger bands. Keep in mind the values are arrived at using two completely different approaches. The plus 2 Bollinger band value is 1707.14 and the implied high using a VIX value of 12.72 is 1706.06. On the low end the minus 2 Bollinger band is 1582.14 and the implied low using a VIX value of 12.72 is 1581.94.
Here is the real point though - to the chagrin of those who disparage High Frequency Trading and the use of algos - the algos may be doing the opposite of what most traders and investors think in that they may be creating price stability even though it may be at levels that are unwarranted based on the macro fundamentals. That assumption is based on the premise that the algos do take into account volatility risk as measured by VIX even while VIX may not be accurately reflecting investor sentiment.
Here is an excerpt from a September, 2011 article in The Hedge Fund Journal that helps to make my point:
In terms of market share, HFT accounts for approximately 60% of US secondary market equity trading and about an average of 35% of total pan European trading (with considerable variation between stocks and countries; see Fig. 1.1). During the volatile days of August, HFT was reported to be 75% of US equity trading making net profits of $60 million in US stock markets on 8 August.
The general consensus amongst market participants today is consistent with the point in this article - in other words HFTs account for the majority of trading volume. The next excerpt - again from the same article deals with real "price discovery" or lack thereof:
Recently, many observers have assumed that price discovery has improved. But evidence to support this is limited. For example, HFT market makers need not just learn passively from observed order flow, but can also strategically set quotes to induce the revelation of information, potentially distorting short and longer term formation. Even the capital asset pricing model has been reviewed. CAPM assumes a frictionless world where price discovery is trivial and risk and return are the two components, yet CAPM ignores the impacts of liquidity, both breadth and depth.
Liquidity transience is also key. With holding periods trending downwards, largely due to the weighted impact of HFT, alterations can occur to the inter-temporal structural changes in stock trading volume and price dynamics. As Zhang stated in 2010, this could "have broad implications for studies that assume volatility, trading volume, or price discovery to be stationary over time (no structural changes are allowed in the classic Fama-MacBeth approach)."
It is rarely doubted that HFT tightens the spread at the first quote on the book, however, questions remain about HFT's impact on market depth. Frequently the size of the bargain at the top of the book is, despite being the best price, the smallest in quantity. Thus 200 shares with a marginal price improvement over a 5000 share order second in line opens the question of HFT's impact on absorption and thus price discovery.
Zhang's seminal study goes on to find that in fact, over the longer term (quarterly periods), HFT hinders price discovery. This finding represented the first trend shift away from other studies which confirmed a positive impact on price discovery, for example, the 2009 study from Hendershott and Riordan. To further elaborate, there is a general view that increased trading activity leads to improved bid ask spreads, and thus, improved price discovery. However, this view tends to overlook the impact of noise trading on the market.
The section on price discovery concludes with this statement:
The self-defined HFT technique of market making, deployment of flickering quotes spread across multiple venues, as well as more passive aggressive forms of noise trading, has led to concepts such as "artificial liquidity" and "disappearing liquidity" entering the lexicon of methods to describe HFT. In turn, they have raised questions over HFT's role in effecting price discovery.
The issue of liquidity in the market is one that I have visited repeatedly in recent months. The points made above are true and indicative of the world we live in today where price discovery is avoided. My point has been that the only way we will see true price discovery is when a number of large traders attempt to exit their trades. At that point we will see true price discovery and what we may find is that there isn't sufficient numbers of buyers to absorb a high volume of sell orders. In other words we may wake up one day and see the market in a free fall the likes of which we have never witnessed before and largely as a result of the distortions in stock price created by the HFT algos.
I want to reference the same article again with this excerpt dealing with the matter of volatility:
Proponents of HFT have long argued that HFT's liquidity provision into the market has the impact of dampening volatility. Some point to the fact that HFT ends the day flat and so cannot impact volatility. However, this ignores what occurs intraday.
Given that stock correlation is positively correlated to volatility Andrew Haldane, Head of Financial Stability at the Bank of England, in his July 2011 study found that "intraday volatility has risen most in those markets open to HFT." Haldane also noted that "HFT algorithms tend to amplify cross stock correlation in the face of a rise in volatility", in effect, stating that in volatile times HFT accentuates volatility given the positive correlation between the two variables. Separately Biais and Wooley found that "(HFT) algorithmic trading could create the scope for systematic risk", potentially opening the debate as to whether or not HFT techniques have the ability to shudder the market before moving it into explosive and potentially contagious scenarios. This concept of HFT adding a volatility layer, over and above the pre-existing fundamental volatility, is increasingly embedded in the body of credible research.
The irony of the statements above regarding volatility is that HFT's do have the impact of "dampening volatility" most of the time but also "in volatile times HFT accentuates volatility". The next excerpt from the same article also supports my thesis that volume is not the same as liquidity:
A final point to note is about the differences between liquidity and volume. Most have said they are one and the same, and in the more traditional sense of understanding they often are. However, in the more contemporary understanding they are not. As the Securities and Exchange Commission and Commodity Futures Trading Commission noted in their joint report into the Flash Crash of 6 May 2010, "high trading volume is not necessarily a reliable indicator of market liquidity."
This relates to the concept now referred to as "disappearing liquidity", where there is a marked imbalance between executable liquidity and net executed volume. This is not always well understood. For example, some execution venues offer members "hit rate" scores as evidence of the benefit of interacting with HFT. From an HFT perspective, the hit rate is the number of times the short term prediction method was correct and within an accepted confidence level. As such, it is no surprise that slower/less sophisticated traders have higher "hit rates" from both the venue and HFT perspective. Whilst what a client "hits" does matter, what a client "misses" is crucial to understanding the real costs of interacting with HFT.
The International Organisation of Securities Commissions took this a step further in their recent HFT consultation document, noting that liquidity could be defined as the ability to "trade in large size quickly, at low cost and when market participants want" . HFT firms are frequently attempting to redefine themselves as "liquidity providers" and yet, HFT does not facilitate the ability to trade in large size quickly, having been shown to increase the total costs of trading and, due to HFT's small quote size and disappearing liquidity, struggle to assist the institutional investor in allowing them to trade when they want. Larry Tabb, CEO of TABB Group exemplified this latter point in discussing recent volatility in the British press when he said: "HFT is indirectly to blame by removing vast swathes of liquidity from the market." Some buy side dealers are now referring to HFT as artificial liquidity providers to emphasize the point.
The underscored portion of the paragraphs above emphasizes a point I have made time and again as it relates to current market structure - the liquidity is not there to handle large orders without crashing the market. The reason is simple - stocks have diverged dramatically from economic metrics and to date the system hasn't been tested to see if it can withstand a high volume exit of existing trades. One only has to ask where will the buyers come from in a market that is fully invested and overleveraged to realize the market impact if that occurs.
To my way of thinking the markets are refusing to act rationally - at least as that term is applied to market action from the historical perspective. There are a number of reasons one could set forth for why we continue to linger at all time highs but one of them is certainly not that current stock price is justified based on improving economic metrics or forward profit expectations.
We are in a different world post recession than we have ever been. Today the HFC algos make up the majority of volume but they don't really represent market liquidity in the traditional sense. These algos are written to account for volatility based on the traditional measures using VIX and it seems apparent that VIX is no longer a reasonable tool for measuring investor sentiment and anxiety. Consequently, the algos keep us confined to a very narrow range at the top of the market even though these prices - in the traditional sense - are unwarranted.
In recent weeks we have seen a more balanced movement in the markets with a tendency to push lower but the algos - not sensing real risk anxiety and fear - continue to employ their VWAP algos to push price back up as the markets move lower. It can be argued that the algos will continue this process until they no longer can due to high volume selling that overwhelms them and turns the algos into selling machines. When that happens is anybody's guess but the recent surge in UVXY outstanding shares suggests that traders and investors are a lot more concerned than market action or VIX suggests. Unfortunately I don't think the algos pay much attention to UVXY and they certainly don't seem concerned about the macro fundamentals.