Markets Move. Get Over It. An Options Volatility Primer

Sometimes the market moves a little. Sometimes the market moves a lot. Why? It might be political unrest in the Middle East. It might be earnings season. It might be the release of economic data. Or the talking heads on TV may have found some story that they can tie to today’s up, down, or stagnant market … Yawn.

Volatility—the measure of the magnitude in the changes of the price of a stock or index—happens. It might seem high, or it might seem low. But no matter what volatility has done, will do, or is doing right now, traders keep on trading. What traders don't do is scratch their heads trying to figure out the cause, and then wait … wait … wait for the perfect volatility scenario to come. Why not? Because it doesn’t exist.

Imagine you’re shooting an arrow at a target, and it’s windy. The wind is going to push that arrow a little bit to the left or right depending on which direction it’s blowing. But you don’t pack up and go home. You aim the arrow a little bit left or right to account for that wind so that, hopefully, the arrow hits the bullseye. Trading in the presence of volatility means you may need to adjust your trading strategy a bit. You don’t quit trading.

But maybe you find some of the volatility talk confusing. That’s completely understandable. No one springs from the womb a full-blown trader or nimble investor. There’s a learning curve. And when the lessons get to volatility, that curve can steepen a bit. The goal of this article is to flatten the curve, get you smarter, and make you more confident in dealing with the inevitable and rarely dull prevailing wind in the trading atmosphere: volatility.

Volatility Jargon

Since we’re not going to be able to avoid the big words, first, here are some terms you’re likely to hear in volatility discussions at your next cocktail party. (Hey, a trader can dream, can’t he?)

Implied Volatility

In my opinion, implied volatility is best learned from back-to-front. The theoretical value of an option is determined using a theoretical pricing model (Black-Scholes, Bjerksund-Stensland, etc.) that requires certain inputs. In particular, the pricing models usually require a current stock price, the strike price of the option, whether it’s a call or a put, the time to expiration, the cost of carrying the stock until expiration, and some volatility number. All the parameters are known (or should be known) except for volatility. So, you plug a volatility number along with the other parameters into a pricing model, and you get a theoretical option price. As you change the volatility input and you keep the other inputs the same, the theoretical option price changes up or down. Now, if you can see the current market price of the option (the average of the current bid and ask, for instance), and you change the volatility input up or down so that the theoretical price is equal to the market price of the option, then you’ve discovered the option’s implied volatility.

The implied volatility of an option is tied directly to the price of the option, specifically, its extrinsic value (time premium). Implied volatility is available only for options. Stocks don’t have implied volatility. Neither do futures. Implied volatility is based solely on current data; it’s not backward looking at all. And traders use it to estimate of the potential volatility of the underlying stock or index in the future. How far in the future? Well, an option is only interested in the underlying stock until expiration. Looking at the implied volatility of options from one expiration to the next, you may see that the implied volatility of an at-the-money option is much higher in a near-term expiration than in a further-term expiration when there is news, like an earnings or news announcement, that is creating short-term uncertainty. When the news comes out, the stock might have a lot of large price changes in the short term, but then settle down once the news has been digested over the long term. The implied volatility of the options in different expirations can reflect that. That’s why I like to think of that volatility wind filling up an option’s extrinsic value like a balloon. When there’s a lot of uncertainty, the wind picks up and the balloon gets bigger, just like extrinsic value. But when the uncertainty dies down, so does the wind; and the balloon deflates, just like extrinsic value.

Don’t be misled by far out-of-the-money options with really high implied vols. Do they indicate the possibility of really huge short-term price changes in the stock? Not necessarily. While a stock or an index can have very large percentage changes in price in a short amount of time, the reason those out-of-the-money options have such large implied vols has more to do with their small prices and low vega, which describes an option’s sensitivity to changes in volatility. All other things being equal, the less time to expiration, the lower an option’s extrinsic value. When there are only a few days left until expiration and the options are so far out-of-the-money that they might be 0.00 bid and 0.01 ask, to have any value at all requires a very high implied volatility, because the vega of those options is very low.

Historical Volatility

Historical volatility is based on the stock or index price over some period of time in the past. It looks at the percentage change in the stock price from one period to the next, whether that period is one year, one day, or one minute. Historical volatility is the standard deviation of those percentage changes, and it indicates the magnitude of the percentage price changes in the past. The trick with historical volatility is the amount of past data you use in the calculation. For example, if you use the past 30 days of price data to calculate the historical volatility of a stock, you’ll likely get a different number than if you used the past 60 days of price data. Because knowing what happened to a stock yesterday isn’t nearly as important to a trade’s profit or loss as what happens to the stock tomorrow, the value of historical volatility is limited by its complete reliance on past data. As they say, past performance is not indicative of future performance. And that’s especially true for the market. But historical volatility can be interesting for comparing the performance of two stocks. For example, if two stocks A and B both rose 10 % in the past year, but B had a much higher historical volatility, that indicates that you would have had a much wilder ride if you held stock B in your portfolio, and perhaps it contributed to more of the swings in profit and loss you had over the past year if you did hold it.

Skew

Ever notice how the implied volatility for options is different from one strike to the next? That’s called skew, and it exists because our models can’t quite figure out how to make the theoretical value of all the options equal to their current market value with one single volatility input. If there’s a lot of uncertainty about what might happen and the market is fearful of a big percentage change, the out-of-the-money options start getting “bid up.” That’s where buyers start buying more and market makers raise their prices in response to the increased demand. Those buyers might be hedgers protecting a large position against a big move, or speculators hoping that the next crash is about to happen. The effect on the volatility of the options is the same. What you see in U.S. equity markets is that the implied volatilities are generally higher the more out-of-the-money the strike is. The implied volatility skew looks like a wide “U” or “V” shape, sometimes tilted in one direction or the other.

Historical vs. Implied

One of the main things people want to see is where implied volatility is in relation to historical volatility. One may be higher than the other, but some traders believe that over time, historical and implied volatilities will move toward each other so their levels are pretty close. I’m not going to judge whether that’s true or not, but in Figure 1 below, you can see that relationship graphically on the thinkorswim^® trading platform from TD Ameritrade.

You can see the two volatilities overlaid on each other on the Charts tab; the studies you’ll want to add are “ImpVolatility” and “HistoricalVolatility.” But there’s a secret to getting them scaled properly to each other: three lines of thinkScript code. Don’t worry, you don’t need to be a programmer. From the top right of any chart, select STUDIES > EDIT STUDIES > STRATEGIES, and look for the “NEW” button in the lower left-hand corner. Type the following code into the NEW SCRIPT box, hit the OK button, and then APPLY:

declare lower;

plot data = imp_volatility();

plotdata2 = historicalvolatilityO;

The default number of days in the historical volatility calculation is 20. To change that in the code to, say, 40, use this:

plotdata2 = historicalvolatility (shortlength = 40);

The “ImpVolatility” study is the Vol Index for the options on a particular stock. It weights the out-of-the-money options for the front two expirations into an overall implied volatility.

Volatility for Strategy Selection

You’re ready to trade and hit the bull’s-eye, but the volatility wind is blowing. How do you account for that with your strategies? It doesn’t have to be complicated when you understand how volatility affects the prices of options and spreads. All other things being equal, higher volatility means the extrinsic value of options is higher. Conversely, lower volatility means the extrinsic value of options is lower. Also, the more time to expiration the option has, the more sensitive it is to changes in volatility. Specifically, strategies that involve shorting options (like covered calls) or shorting spreads (like verticals or iron condors) generate smaller credits when volatility is lower. Because the credit comprises the potential profit of those trades, the lower volatility makes the max risk higher and the potential profit lower, given the same strike prices and days to expiration. On the other hand, strategies like calendar spreads can have lower debits when volatility is low. That decreases their maximum risk. A trader may bias her trades toward doing more calendar spreads, say, and fewer short verticals when volatility is lower. When volatility is higher, she may put on fewer calendar spreads and more short verticals.

Volatility for Position Sizing

From a risk management perspective, an option trader or stock investor may adjust his position size depending on volatility. When volatility is high and there’s lots of uncertainty spooking the market, reducing the size of your positions can be prudent. Now, here’s a trick question: When volatility is lower, do you increase your position size? Not necessarily. Generally, you should have some maximum amount of risk in mind that you’re not willing to go beyond. No matter how low volatility gets, you should not exceed that number. So, if you’ve reduced your positions from that max risk amount when volatility is high, you might want to increase your positions closer to the max amount when volatility drops.