The Inertia of Volatility

Sir Isaac Newton said that an object in motion tends to stay in motion unless acted upon by another force. Volatility acts much the same way. Most stocks tend to trade with a certain measurable amount of daily price fluctuations.
This can be observed by looking at the stock’s realized volatility. If there is no outside force—some pivotal event that fundamentally changes how the stock is likely to behave—one would expect the stock to continue trading with the same level of daily price movement.

This means IV (the market’s expectation of future stock volatility) should be the same as realized volatility (the calculated past stock volatility).But just as in physics, it seems there is always some friction affecting the course of what is in motion. Corporate earnings, Federal Reserve Board reports, apathy, lulls in the market, armed conflicts, holidays, rumors, and takeovers, among other market happenings all provide a catalyst for volatility changes. Divergences of realized and implied volatility, then, are commonplace.

These divergences can create tradable conditions, some of which are more easily exploited than others.To find these opportunities, a trader must conduct a study of volatility.Volatility charts can help a trader visualize the big picture. This historical information offers a comparison of what is happening now in volatility with what has happened in the past.

The following examples use a volatility chart to show how two different traders might have traded the rush and crush of an earnings report.Volatility Selling:Susie Seller, a volatility trader, studies semiconductor stocks.Exhibit 12.3 shows the volatilities of a $50 chip stock. The circled area shows what happened before and after second-quarter earnings were reported in July.The black line is the IV, and the gray is the 30-day historical.

In mid-July, Susie did some digging to learn that earnings were to be announced on July 24, after the close. She was careful to observe the classic rush and crush that occurred to varying degrees around the last three earnings announcements, in October, January, and April. In each case, IV firmed up before earnings only to get crushed after the report. In mid-to-late July, she watched as IV climbed to the mid-30s (the rush) just before earnings.

As the stock lay in wait for the report, trading came to a proverbial screeching halt, sending realized volatility lower, to about 13 percent. Susie waited for the end of the day just before the report to make her move. Before the closing bell, the stock was at $50. Susie sold 20 one-month 50-strike calls at 2.10 (a 35 volatility) and bought 1,100 shares of the underlying stock at $50 to become delta neutral.Exhibit 12.4 shows Susie’s position.

Her delta was just about flat. The delta for the 50 calls was 0.54 per contract. Selling a 20-lot creates 10.80 short deltas for her overall position.After buying 1,100 shares, she was left long 0.20 deltas, about the equivalence of being long 20 shares. Where did her risk lie? Her biggest concern was negative gamma. Without even seeing a chart of the stock’s price, we can see from the volatility chart that this stock can have big moves on earnings.

In October, earnings caused a more than 10-point jump in realized volatility,to its highest level during the year shown. Whether the stock rose or fell is irrelevant. Either event means risk for a premium seller.The positive theta looks good on the surface, but in fact, theta provided Susie with no significant benefit. Her plan was “in and out and nobody gets hurt.”

She got into the trade right before the earnings announcement and out as soon as implied volatility dropped off. Ideally, she’d like to hold these types of trades for less than a day. The true prize is vega. Susie was looking for about a 10-point drop in IV, which this option class had following the October and January earnings reports. April had a big drop in IV, as well, of about eight or nine points.

Ultimately, what Susie is looking for is reversion to the mean.She gauges the normal level of volatility by observing where it is before and after the surges caused by earnings. From early November to mid- to late- December, the stock’s IV bounced around the 25 percent level.

In the month of February, the IV was around 25. After the drop-off following April earnings and through much of May, the IV was closer to 20 percent. In June, IV was just above 25. Susie surmised from this chart that when no earnings event is pending, this stock’s options typically trade at about a 25 percent IV.

Therefore, anticipating a 10-point decline from 35 was reasonable, given the information available. If Susie gets it right, she stands to make $1,150 from vega (10 points 3 1.15 vegas 3 100). As we can see from the right side of the volatility chart in Exhibit 12.3, Susie did get it right. IV collapsed the next morning by just more than ten points.