The Webster Dictionary defines an anomaly as “something that is unusual or unexpected, a deviation from the rule.”
However, if observed anomalies continue to rise in frequency, are they still anomalies?
This is the debate many market participants have when analyzing recent returns.
For example, the daily returns and standard deviation (“sigma”) of the S&P 500 over a 60-year+ period (source: CFA Institute) demonstrates how close observable returns have been to the normal distribution.
Unfortunately, assessing potential market movements from average returns and standard deviations is only part of the picture. Evaluating average returns and standard deviations masks extreme movements, either positive or negative.
There are several forms of distributions that aren’t normally distributed, where observations are scattered over a wide range or clusters of observations are in a single area. In statistical parlance, the stock market trades in what is known as a “leptokurtic” distribution. In other words, many observations are clustered around the center. This produces a distribution with a very high peak.
This type of distribution also produces the “fat tails,” or observations far from what is “expected.” In short, most observations are clustered around the mean with a greater likelihood of large fluctuations within the fat tails.
According to the CFA Institute, occurrences of multi-sigma events, defined as moves that are three standard deviations or more, have been on the rise since 2000. As can be seen from the table below, occurrences of monthly moves to the downside by greater than -5% since 2000 have increased to 13% of observations versus other periods which range from 7.83% to 10.09%. There has also been a slight uptick in monthly moves greater that -9% since 2000 but a decrease in +5% moves.
There are a few likely factors behind this change in market dynamics. First, the elimination of the uptick rule by the SEC in July 2007 has exacerbated the effects of algorithmic trading. The uptick rule required every short sale to be entered at a price higher than the previous tick.
The growth in algorithmic trading has been staggering and one must question whether the increased moves in the market could be directly related to this. If the uptick rule were still in place, would algorithmic trading have become such a force in today’s markets?
The original reason for the uptick rule was to provide stability and assuage potential market panics. The uptick rule had been in place since 1938, but many supported its elimination in 2007. However, a cry began quickly on Wall Street as market volatility began to increase and multiple calls for reinstatement surfaced. In 2010, an alternative uptick rule was implemented, but only restricts short-selling after a stock has declined by more than 10%.
Second, market structure has become more fragmented with approximately 11 electronic exchanges comprising the majority of daily stock volume, taking significant share away from human specialists at the NYSE. This has resulted in thinner liquidity for individual stocks, especially during periods of market stress, which has possibly made large moves occur more often. However, the volume and liquidity of ETFs and options on ETFs has improved tremendously as usage of ETFs and options has grown in the past decade. We expect ETFs will continue to benefit from this growth.
If this is the new reality, what can be done about it? Attempting to miss short-term adverse multiple sigma events to the downside can be a daunting, if not impossible, challenge. Side-stepping short-term sell-offs is akin to trying to dance between the raindrops. In addition, missing the recoveries can be equally devastating to a long-term portfolio. However, by implementing certain option strategies, holders of ETFs can help insulate their portfolios from market volatility.
True, the probability of a particular multi-sigma event occurring at a given point in time is less than 1%.
However, the likelihood of some multi-sigma event occurring at some point in the future is 100%. The key is to be prepared for them when they do occur. In addition to having sound, time-tested rules for managing a portfolio of ETFs, it could be beneficial to overlay option-based hedging strategies that can help mitigate potential losses of a downside multi-sigma event. Successfully implemented, option-based hedging strategies can alleviate possible losses and lower the standard deviation of the overall portfolio.
The nature of innovation is disruption. As the financial industry innovates and evolves there will be positive and negative consequences. It seems unlikely anyone would have foreseen the dominant role ETFs would play in portfolios when they first hit the market in the early 1990’s. Likewise, it is unlikely anyone would have foreseen the increased volatility due to changes in the exchanges and regulatory environment. If these changes are here to stay, continued innovation is required to manage the new risks in a changed world.
Chris Hausman is a Senior Trader and the Chief Market Technician at Swan Global Investments, a participant in the ETF Strategist Channel.