In option pricing, you have your known information (time to expiration and price of the underlying) and you have your unknown information. You also have intrinsic value (how much money the option will be worth at expiration) and extrinsic value (how much you have to pay for the option minus the intrinsic value). Extrinsic value has two main components, time to expiration and implied volatility.
Implied volatility is by far the most misunderstood and most important aspect of options trading. Implied volatility has huge impact of an options price and proper understanding can be the difference between being successful and unsuccessful.
Let’s begin this discussion with the definition:
- Implied – suggested but not directly expressed.
- Volatility – ability to change rapidly and unpredictably.
If we put those two words together and in the context of trading, Implied Volatility is – the suggested, but not directly expressed, ability of an asset’s price to change rapidly and unpredictably.
A question comes to mind, who is implying this ability of prices to change? I know a lot of traders believe that market makers set implied volatility, which in turn sets option prices, but this is not the case. Option traders themselves set implied volatility.
Think about it this way, what causes the prices of a stock or a future to change? Buying and selling. Lets suppose a stock has a good earnings report and moves up 5%. What caused that price to move? We can break it down to minute parts, positive earnings mean more investors want to own this stock, and less sellers are willing to sell this stock. So the prices go up to the point where investors that already own the stock are willing to sell it to the new buyers of the stock.
The converse happens when a price drops, bad earnings report, less buyers want to buy the stock, more investor want to sell the stock, so the price goes down to where new buyers are willing to buy the stock from investors that want to sell it.
But what happens when there is an imbalance between the buying and selling of options? Options derive their value from another asset, called the underlying. But options after all are trade able assets. So it would stand to reason that if there is more investors willing to buy an option than investors willing to sell the option, the price will go up. Regardless of what the underlying is doing. This is the essence Implied Volatility.
If there are more buyers of an underlying’s options than sellers, the price will go up, causing implied volatility to go up. Conversely, if there are more sellers, the price will drop and so will implied volatility. So the implied aspect comes from the option traders themselves and at what price they are willing to buy or sell a given option.
This is a very important takeaway. Option Prices are set by Option Traders, and Implied Volatility is calculated using option prices. Below is a link to an implied volatility calculator. Click on the link and set it up on a real life option. Notice that option price is a variable used to calculate implied volatility.
What does Implied Volatility tell us?
Before we get to far into this discussion, and this should go without saying, stocks with higher implied volatility are more likely to have bigger moves than stocks with lower implied volatility. The chart below is of FXE, it is currently posting an implied volatility index of 4.75%. It started the last year at $108 per share. and is currently trading at $105.70. It does not move very much.
The chart below is of EA. It is also trading at $105.70 per share. But it has an Implied volatility index of 22.08%. Notice it started the year at $80 per share. Notice it has quite a bit more movement than FXE.
What do Implied Volatility calculations mean?
If there is a stock with an implied volatility of 50%, what is that really telling us?
Above is the formula of the Black-Scholes Model of option pricing, don’t worry we are not going to go through this. But we should have some knowledge of what the outputs mean. Standard deviation is something that anyone trying to employ high probability option strategies should be familiar with.
Standard Deviation is the amount of variation within a set of events. It can be used for anything that has a set of events. One Standard Deviation is 68.2% of occurrences will fall within a that range. Lets say I drop 100 marbles onto the target below. The point where 68% of the marbles will land closest to the center of the circle would be considered one standard deviation.
One Standard Deviation is 68.2%, Two Standard Deviations 95% Three Standard Deviations is 99.7%.
How does this translate to implied volatility and high probability options trading? The theory goes, 68.2% of the time, over a one year time period, a stock will trade within it’s implied volatility up or down. Lets say that stock ABC is trading at $100 per share and has an implied volatility of 25%. That means that over the next year with a 68.2% accuracy, ABC will trade in between $75 and $125.
Lets say Stock DEF is also trading for $100 per but has an implied volatility of 50%. Over the next year, with an accuracy 68.2% DEF will trade in between $50 and $150.
To find the 1 standard deviation the formula is:
Current Price x Implied Volatility for the option expiration x Square Root of Days To Expiration/365.
Lets run through some real world examples. At the time of writing SPY DEC 2020 options had an Implied Volatility of 18.7%, it’s price was 317.32, and has 370 days to expiration.
317.32 x .187 x square root of 370 / 365 = 59.93.
So over the next year, SPY is expected to trade in between 257.39 and 377.25 with a 68.2% accuracy.
Let’s run this back from last year and see how SPY did in 2019. On December 19th 2018 SPY was trading at 251.26. The DEC. 20 2019 options had an Implied Volatility of 23.1%, 365 days until expiration.
251.26 x .231 x square root of 365/365 = 58.04. The expected range for SPY from DEC. 19th 2018 to DEC. 20th 2019 was 193.22 and 309.03. The SPY December 2019 options just expired with SPY trading at $320.73. This year SPY exceeded it’s one standard deviation move to the upside by $11.70.
Let’s do something with a little higher implied volatility and less time til expiration.
ROKU is trading at 132.49, the Jan 17 2020 expiration has an implied volatility of 66.1% with 33 days til expiration.
132.49 x .661 x square root of 33/365 = 26.27. There is a 68.2% chance Roku will stay within 106.22 and 158.76 before the Jan 17 2020 expiration.
If you use Tastyworks, they automatically calculate the 1 and 2 standard deviation move and put it right in the option chain.
The dotted blue line in the screenshot above, is what level the 1 standard deviation resides on the Tastyworks option chains. This is going to be very useful when putting trades together.
What are some Causes that Change Implied Volatility?
There are lots of things that change implied volatility. Since implied volatility is set by the trading of options, whatever causes investors to buy or sell options will impact it.
The chart below is of LULU with implied volatility as the indicator on the bottom. Notice that implied volatility rises until an earnings announcement. Then after the announcement implied volatility drops drastically.
So what is happening here? Traders are buying options at a normal rate and slowly increasing option buying activity into earnings announcements. Once the earnings announcement is released traders rush to sell their options, causing option prices to drop thus causing implied volatility to drop.
Implied volatility also goes up when markets fall, due to more investors buying options to hedge positions in times of uncertainty.
The chart above of the SPY illustrates that when the market declines implied volatility increases.
To recap , Implied Volatility is set by the trading of options. Stocks with higher implied volatility have bigger price moves than stocks with lower. We can calculate the anticipated movement of an underlying based on implied volatility. Implied volatility drops after an earnings report. And implied volatility goes up when markets fall.