Intermediate
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Options Theory: What is Implied Volatility Rank?

December 3, 2017

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We’ve previously explored the topic of implied volatility (see here and here). But today I want to touch on an indicator built around implied volatility that you can use to determine if options are cheap expensive quickly. We’re talking about implied volatility rank or IVR for short. Some traders refer to it as IV Percentile. Because it equalizes the implied volatility number, it allows you to compare how expensive options are in one stock versus another.

Remember, implied volatility is derived from an option’s premium. When demand rises, premiums inflate driving implied volatility higher in the process. When demand falls, premiums drop dragging implied volatility lower.

The most common usage of implied volatility is to help with strategy selection. Remember there are multiple ways to acquire bullish (or bearish) exposure on a stock. You can buy calls, sell puts, or initiate some type of spread trade. Deciding which is most appropriate could come down to personal preference, the potential risk and reward, or whether options are cheap or expensive. It’s the last metric that traders rely on implied volatility rank for.

Simply put:

  • When IVR is high, options are expensive, and selling puts or put spreads is very attractive.
  • When IVR is low, options are cheap, and selling puts or put spreads aren’t as appealing.

Let’s talk about how IVR is constructed

It looks at the one-year range of implied volatility and sets the highest reading at 100 and the lowest reading at 0. Then, it expresses the current volatility reading as a percentage of that range. For example, let’s say AAPL implied vol has traded between 10 and 30 this year. And right now it’s sitting right in the middle at 20. If we set the high of the range (30) to 100 and the low of the range (10) at 0, then the current reading of 20 would translate into an IVR of 50%. In other words, Apple’s current implied volatility sits at the 50th percentile.

IV Percentile on TOS (Thinkorswim)

Here’s another example, let’s say Wal-Mart’s implied vol has traded between 5 and 15 over the past year. And its current reading is at 14. Now, if we just looked at Wal-Mart’s implied vol of 14% and compared it to Apple’s implied vol of 20%, we may come away with the impression that Apple options were more expensive than Wal-Mart’s. But they’re not! At 14%, WMT volatility is in the 90th percentile of its one-year range. Apple, on the other hand, was only in the 50th percentile. Make sense? That means WMT would be a more attractive candidate for a short premium strategy than AAPL.

Comparing one stock’s implied volatility to another isn’t apples-to-apples. Comparing one stock’s implied volatility rank to another is an apples-to-apples comparison!

By adding IVR as a column heading in your watchlist, you can sort your entire universe of stocks by how expensive their options are. Those with the highest IVR offer the most pumped-up premiums. You’ll be able to sell further OTM options with higher potential reward than those with low IVR.

I did that very exercise this weekend with my ETF list and found that the China ETF (FXI) carried the highest rank with 94%. That means FXI options are just about as expensive as they’ve been at any point this past year. So if I’m looking to enter bullish trades do you think I’m leaning toward buying options or selling them?

Selling!

Right now with FXI trading at $45.81, I can sell a $42 strike put for 50 cents. That places my break-even at $41.50 which means as long as FXI doesn’t fall by more than 9.4% over the next month, I will capture a profit. Since the margin requirement is around $500, the potential return on investment is 10%. That’s a great naked put trade! If the implied volatility rank were lower, I might have only been able to sell the $44 or $43 strike put for 50 cents.

$FXI

If you haven’t already, you should add IVR to your watchlist and as an indicator on your charts. It’s a useful tool for spotting the juiciest premiums on the Street.

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4 Replies to “Options Theory: What is Implied Volatility Rank?”

  1. MARIADIAMOND says:
    December 4, 2017 at 4:24 pm

    For those who wonder how to add it:
    https://www.youtube.com/watch?v=lkxVvyBMGkE

    To add just a column to a watchlist:
    1. Click on the wheel at your watchlist
    2. Customize
    3. Select Custom1 and add it to the list “Current Set”
    4. Name it “IVR” as an example
    5. Go to ThinkScript Editor and delete everything (1line) what’s there
    6. Copy/Paste code:

    declare lower;
    declare hide_on_intraday;

    #IVPercentile
    def vol = imp_volatility();
    input DisplayIVPercentile = yes;
    input DisplayImpVolatility= yes;
    input DisplayDaily1StandardDev = yes;
    input DisplayWeekly1StandardDev = yes;
    input DisplayMonthly1StandardDev = yes;

    input TimePeriod = 252;

    def data = if !isNaN(vol) then vol else vol[-1];
    def hi = highest(data, TimePeriod);
    def lo = lowest(data, TimePeriod);
    plot Percentile = (data – lo) / (hi – lo) * 100;
    def lowend = Percentile 50;

    Press OK, Apply.

  2. FADIHATTENDORF says:
    December 6, 2017 at 9:15 am

    Hi Tyler,
    this is very interesting and helpful. Thank you for the report.
    I’m not sure what I did not do correctly because of the message related to “def lowend = Percentile 50;”
    that says, “Invalid statement: def at 18:1”
    How can I correct the message?
    Thank you.
    Fadi

    1. Mak says:
      July 11, 2018 at 5:58 am

      I’m getting the same message Fadi!

      were you able to resolve?

  3. adam_stewart5317 says:
    February 5, 2019 at 11:56 am

    declare lower;
    declare hide_on_intraday;

    #IVPercentile
    def vol = imp_volatility();
    input DisplayIVPercentile = yes;
    input DisplayImpVolatility= yes;
    input DisplayDaily1StandardDev = yes;
    input DisplayWeekly1StandardDev = yes;
    input DisplayMonthly1StandardDev = yes;

    input TimePeriod = 252;

    def data = if !isNaN(vol) then vol else vol[-1];
    def hi = highest(data, TimePeriod);
    def lo = lowest(data, TimePeriod);
    plot Percentile = (data – lo) / (hi – lo) * 100;
    def lowend = Percentile 50;

    #Labels
    addlabel(DisplayIVPercentile , concat(“IV Rank: “,aspercent(Percentile /100)), if lowend then color.red else if highend then color.green else color.yellow);

    addlabel(DisplayImpVolatility, concat(“ImpVolatility: “,aspercent(vol)), if lowend then color.red else if highend then color.green else color.yellow);

    def ImpPts = (vol / Sqrt(252)) * close;
    AddLabel(DisplayDaily1StandardDev , Concat(“Daily 1 SD +/- $”, Astext( ImpPts, NumberFormat.TWO_DECIMAL_PLACES)), if lowend then color.red else if highend then color.green else color.yellow); ;

    def ImpPts2 = (vol / Sqrt(52)) * close;
    AddLabel(DisplayWeekly1StandardDev, Concat(“Weekly 1 SD +/- $”, Astext( ImpPts2, NumberFormat.TWO_DECIMAL_PLACES)), if lowend then color.red else if highend then color.green else color.yellow); ;

    def ImpPts3 = (vol / Sqrt(12)) * close;
    AddLabel(DisplayMonthly1StandardDev, Concat(“Monthly 1 SD +/- $”, Astext( ImpPts3, NumberFormat.TWO_DECIMAL_PLACES)), if lowend then color.red else if highend then color.green else color.yellow); ;

    plot LowVol = 25;
    plot HighVol = 50;

    LowVol.SetDefaultColor(GetColor(5));
    HighVol.SetDefaultColor(GetColor(6));

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