Making Sense of the Three Types of Volatility


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Chief Strategist at Interactive Brokers

Pretty much anyone can tell you that markets have been volatile. Far fewer can tell you how to evaluate that volatility.

It was obvious that investors were extremely fearful when the Cboe Volatility Index, or VIX, closed above 80 earlier this week, but only those who truly understand volatility measurements can grasp the ramifications of that extraordinary value. In times like these, anyone who trades or invests with options should fully comprehend such measurements.

It’s time for a quick refresher course. The most common volatility measures used in options pricing are rooted in the statistical concept of standard deviation. In a market context, this measures the dispersion of a security’s returns around its average. Two stocks may have similar mean returns, but one may have larger up and down moves. That stock would have a higher standard deviation. This dispersion of returns, measured over time, is the basis of the concept of historical volatility.

The concept of implied volatility is perhaps the most important to options pricing. It is related to historical volatility and expressed in similar terms, but is actually an algebraically derived number, rather than a real-world measurement. Options prices frequently move somewhat independently from those of their underlying stocks. So, traders realized that if we start with a given options price and separate all the visible inputs, the remaining variable is the implied volatility of that option.

Options traders are speculating on a third concept, realized volatility—the level that a trader experiences during the holding period of an option. In effect, it is the historical volatility reading that will be in place when the option expires or is sold. Buyers are betting that the realized volatility on their options exceeds the implied volatility at the time of purchase; writers (sellers) are speculating on the opposite.

Confusingly, these measures are usually expressed in annual, not daily, terms. The Black-Scholes options-pricing model uses annualized volatility in its calculations. It is of little practical value, however, to think in terms of annual volatility when the vast majority of options expire in days, weeks, or months, not years. Knowing that a stock has a reasonable likelihood of a 40% move over the course of a year isn’t valuable information to someone buying or writing an option that expires within three weeks.

Fortunately for options traders, it is quite easy to convert those annualized volatility measurements into daily values. To do so, divide the annualized number by the square root of the number of business days in a year. That results in a divisor very close to 16. This “Rule of 16” allows us to demystify volatility, letting professionals and individual investors alike to better assess short-term trading strategies.

A stock with an annualized volatility reading of, say, 40 has a daily volatility of 2.5%. If I am considering writing a three-week call on that stock, I find it much easier to conceive of that stock’s likelihood of price changes averaging 2.5% a day over the next three weeks than its prorated likelihood of a 40% move in that period.

We now have the tools to better evaluate this week’s 80 VIX reading. The VIX is constructed to provide the market’s expectation of 30-day volatility; thus 80, when divided by 16, implied that options on the S&P 500 were expecting roughly 5% daily moves over the next 30 days.

In light of recent market movement, that historically high level doesn’t appear all that unreasonable. This type of thinking is also helpful in advance of earnings and other events. The short-term option with a 40 volatility is anticipating a 2.5% average daily move. It is relatively easy to consider whether an earnings release is likely to boost or drive down a stock by that amount.

Steve Sosnick is chief strategist at Interactive Brokers and head trader of its Timber Hill subsidiary.

Originally Posted on March 19, 2020 – Making Sense of the Three Types of Volatility

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