How to Evaluate Implied Volatility Correctly

By TradeSmith Editorial Staff

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Options have got to be one of the coolest trading products out there.

Once you dig into them and learn the ins and outs, they open up a world of possibilities.

You see, we get to choose when we buy and sell options contracts. And by selling when prices (premiums) are high and buying when they’re low, we create an edge.

That edge comes from evaluating the demand for options, also known as implied volatility (IV).

However, many retail traders don’t do this correctly, and it costs them a lot of money.

I want to show you the right way to analyze implied volatility, starting with why it matters, how to measure it, and then breaking it down to the individual types.

Why Implied Volatility Matters

Options prices are based on three major factors:

  1. The time between now and the expiration date
  2. The distance between the strike price of the option and the stock’s current price
  3. The implied volatility
(Yes, interest rates and dividends influence stock prices, but we’ll ignore those for now.)

Implied volatility is the only component influenced by the actions of options traders.

And unlike stocks, implied volatility is mean-reverting, meaning it tends to move back toward its average.

In the chart below, I mapped out the CBOE Volatility Index (VIX), which tracks volatility of the S&P 500. Each candlestick represents the trading range of that day.

Source: TradeSmith Finance

What you’ll notice is that on average, the price for the VIX tends to come in around $18. Historically, it ranges between $15 and $18. This is mean-reversion.

The tendency for high implied volatility to trend back towards the mean is why option traders prefer to sell options when implied volatility is high and buy options when implied volatility is low, regardless of whether we’re talking about puts and calls.

Here’s a very simple example.

Let’s say the option price for a stock is $5. The components for that price break down as follows:

  • Time until expiration — $2
  • Distance between the strike price and current stock price — $2
  • Implied volatility — $1
Now, if implied volatility suddenly shoots up, that component may contribute $4 instead of $1 to the option’s price, bringing the total option price to $8.

If that marks an extreme in implied volatility, we want to sell the option. Based on history and probabilities, that $2 implied volatility should trend back toward $1, everything else being equal.

So the next question is, how do we know when implied volatility is high, low, or average?

Measuring Implied Volatility

Most traders measure implied volatility in one of two ways: implied volatility percentile and implied volatility rank.

Implied volatility percentile looks at the implied volatility for each day over the last year and tells you the percentage of days where implied volatility was below the current implied volatility.

For example, let’s say that the current implied volatility is 60%. Your other data includes days that were 10%, 20%, 50%, 80%, 75%, and 65%.

In this case you have three days below the current implied volatility and three days above, making your implied volatility percentile 50%. You can think of this in terms of ACT/SAT scores, where the number itself doesn’t matter as much as how it compares against others. With a percentile score, we’re comparing the current implied volatility’s place within the range of all other IVs over the course of a year.

That’s all well and good. But it doesn’t really tell you how far ahead you are.

Implied volatility rank looks at the implied volatility range over the last year and calculates where the current implied volatility lands in that range.

Let’s say that over the last year, implied volatility reached a high of 80% and a low of 20%. Currently, it sits at 45%.

Think of it like grading the implied volatility on a curve. If 80% is the highest implied volatility, our implied volatility rank says that the current implied volatility is 41.67% of the way between 20% and 80%. Implied volatility rank is the better measure because it is less susceptible to sustained periods of low or high volatility.

For example, let’s say a stock has an implied volatility range from 20% to 30%. Most of the time, the stock traded between 20% and 21%.

If the stock finds itself at 22% one day, the implied volatility percentile might show 90%. That doesn’t really tell us how far away from the mean we are, whereas the implied volatility rank of 10% would say there isn’t much room for implied volatility to contract.

Types of Implied Volatility

Now I’m about to share something with you that most traders never talk about.

There are three different types of implied volatility: market, stock, and option.

Market volatility is what we hear about on the news and when we discuss the VIX. This is the implied volatility at the aggregate market level.

Next, we have implied volatility for each individual stock.

What you need to understand for both of these types of implied volatility is:

  • They measure aggregate implied volatility across all the options.
  • The implied volatility is typically tied to the closest options that are 30 days until expiration.
This is completely different from the implied volatility of individual option expirations and strike prices.

Let me explain through the use of an options chain.

Source: Thinkorswim

This is an options chain for Apple (AAPL).

Down the left side you will see the different expiration dates for the options contracts (yellow).

Down the right side you will see the different implied volatility percentages for each expiration (orange). Notice that the percentage is different for each expiration cycle.

In the expanded portion for the March 18, 2022, expiration, you can see different implied volatilities for each strike price (red). Notice how none of them match the 31.62% implied volatility listed at the top of all the strikes? That 31.62% is the implied volatility across all the options in that chain (this number is calculated from all the IVs within that expiration’s chain).

I know this seems confusing, so bear with me, as I’m about to bring it all together.

Here’s what you need to know:

  • When evaluating the implied volatility rank for any strike price, use the implied volatility for the expiration cycle for your calculation.

  • Implied volatility will vary between expiration cycles on the same stock.
  • It will also vary between strikes for any given expiration, increasing the further out of the money you go and decreasing the further in the money you go.
Now, are you ready for a neat trick?

When you find a stock with a high implied volatility rank, you can estimate the contraction in implied volatility.

Simply look at implied volatility for expiration dates nine to 12 months out from the expiration you’re looking at and compare those to the current cycle.

Here’s an example using Cisco (CSCO), which reports earnings on Feb. 16.

Implied volatility almost always increases leading into earnings because traders want protection against potential post-earnings moves.

After the earnings announcement, implied volatility decreases.

The Feb. 18, 2022, option chain implied volatility is 40.36%. If we go out 137 days to the June 17, 2022, option chain, implied volatility is 31.37%.

Source: Thinkorswim

So if you were to sell options that expire after earnings, you could assume that implied volatility would contract almost 9%, all else being equal. By knowing how the implied volatility is likely to move, you can make more informed decisions about selling (or buying) options contracts based on how the volatility is likely to impact your contract’s premium.

Pretty neat, huh?

Now, I know it’s not that simple, because stocks can and do move after earnings and with the broader market. However, if you did this type of trade often enough, you would build an edge simply by selling options when implied volatility is high.

With many of you at different points in your options trading careers, what are some option topics you want to hear more about?

Email me and let me know. While I can’t respond to everyone, I promise I read all the emails.