Understanding Implied Volatility in Options

What's going on YouTube? In this video, I'm going to teach you to become a master of implied volatility because I'm going to clearly explain to you what implied volatility represents, and I'm also going to teach you some of the most common topics regarding implied volatility, such as IV rank and IV percentile, why implied volatility changes, and some of the things that you're going to observe around earnings reports with implied volatility. After this video, you're going to have a solid understanding of what implied volatility actually represents, and I'm fairly confident that you're going to realize that implied volatility is not as complicated as it may seem at first. Stay with me. Implied volatility can be an extremely confusing topic as a beginner, and I know this firsthand because when I first got into options trading, the first time I saw the words implied volatility, I thought that I would never truly understand what those words meant because it seemed like such a common word. complex topic. In this video, I'm going to show you that it's not as complicated as it seems as implied volatility is pretty intuitive once you get the hang of it. So let's get started. First and foremost, what exactly is implied volatility? In the simplest terms possible, implied volatility represents the amount of volatility that is generated by represents the market's expected magnitude for a stock's future price movements. Implied volatility stems from a stock's option prices, which are implying how much volatility is expected from that stock going into the future. Let's look at a couple of examples of some real option prices on stocks from historical dates so I can demonstrate to you exactly what I mean by the option prices implying future volatility in that stock. Consider the following option prices that I recorded from two similarly priced stocks, which at the time were Pepsi and U.N.P. In this table, we're looking at the call option and the put option that are slightly above and below the stock price at the time of recording their prices. As we can see, Pepsi was at $102 and the $105 call was $0.80, while the $100 put was $1.17. At the time of recording these option prices, Pepsi's implied volatility in the 37-day expiration cycle was 16.4%. With U.N.P. at roughly the same price as Pepsi, we can see that the $105 call was $0.80. $2.72 and the 100 put was $1.92. At the time of recording these option prices, UNP's implied volatility in the 37-day expiration cycle was 30.9%. So the first key concept that I want you to understand here is that implied volatility comes from a stock's option prices, and a common misconception, especially for beginner options traders, is that the option prices are coming from implied volatility. When we trade options, we're trading the option contracts themselves. we're not trading the implied volatility number. By trading the option contracts, the option prices will change from day to day, and based on the changes in those option prices, based on the buying and selling pressure that's currently being observed in the marketplace, implied volatility is going to adjust according to those changes in the option prices. When comparing the Pepsi and UMP options, we can see that the higher UMP option prices, relative to the time until expiration, results in a higher implied volatility reading. In other words, because we're comparing two similarly priced stocks and those stocks have different levels of implied volatility, by looking at the option prices we can figure out why those implied volatility levels are different. The higher UNP option prices tell us that the market is implying more expected stock price volatility compared to Pepsi because the options in Pepsi are cheaper than the options in UNP and both of the options have the same amount of time until expiration. But it's not the options overall price that gives us implied volatility, it's actually the extrinsic value that exists in the stock's options. In other words, implied volatility represents the amount of extrinsic value that exists in a stock's options relative to the time they have until they expire. Let's look at some real-time examples and compare some similarly priced stocks looking at the options on each stock to determine which one has higher levels of implied volatility. To do this, I'm going to use the Tastyworks trading platform, so let's go ahead and hop onto the platform and look at some option prices. If you're unfamiliar with Tastyworks, be sure to check out the link in the description. description if you'd like to know more about their technology and their commission structure. I've just opened up the Tastyworks trading platform and I'm gonna run through this very quickly to compare the option prices on two similarly priced stocks with the same amount of time until expiration. The two products I'm going to compare are SPY which is the S&P 500 ETF and then we're gonna look at Adobe because both of these stocks are right around $292. So to get started I'm gonna open up the September options with 49 days to expiration. and I'm going to look at the price of the 290 straddle. As we can see here on SPY, this straddle is trading for $15 and the extrinsic value is right around $1,310. This is giving us an implied volatility of about 18%, but keep in mind it's not this particular straddle, but we're just going to compare the implied volatility. and the extrinsic value of these two straddles. So if I go to Adobe, open up the September options with 49 days to expiration, and I queue up the 290 short straddle, we can see that this straddle is trading for $27 and the extrinsic value that exists in this particular straddle is 2,500. and with the increase in extrinsic value compared to SPY, we would expect Adobe to be trading with higher levels of implied volatility. If we look to the top right here, we can see that Adobe in the September expiration cycle, these options are giving us an implied volatility of 33.7%. When market participants trade options, they are either buying options or selling options. When option buyers are willing to pay more for a stock's options and option sellers demand more premium for selling a stock's options, that's an indication that the market is anticipating lots of volatility from that stock price in the future. Conversely, when option buyers are not willing to pay as much for those options and option sellers will collect less... premium to sell those options, that's an indication that the market is not anticipating a lot of volatility from the stock price in the future. And we know that because the option buyers are paying less for the options, but more importantly, option sellers are willing to accept lower premiums for taking the risk by selling those options. So this begs the question, what makes traders more or less willing to pay higher premiums for a stock's options? In other words, why do a stock's option prices experience wide price fluctuations and therefore big changes in implied? volatility from time to time. Generally speaking, there's a very close relationship between a stock or product's recent volatility or historical volatility and the level of volatility that is expected into the future. And in other words, there's a close relationship between a stock's historical volatility or how volatile the stock has been in recent periods and the option prices on that stock. To prove this, I plotted the one month historical volatility of the S&P 500 against the levels of the VIX index after recording those levels of observed volatility. The VIX index measures one month option prices on the S&P 500 index, so by comparing the S&P 500's historical volatility to the VIX index, I can draw a conclusion as to whether or not historical volatility has any impact on the option prices on the S&P 500. And in other words, I'm trying to see if there's any relationship between the historical volatility of the S&P 500 and the future expected volatility of the S&P 500, which is implied through the option price. prices on the S&P 500 index. As we can see, there's a very clear relationship between the S&P 500's historical volatility and the one month option prices as measured by the VIX index. When the recent volatility in the S&P 500 was at lower levels, so was the VIX index, implying that when the S&P 500 was not as volatile, the option prices were cheaper, meaning that when the S&P 500 was experiencing low levels of volatility, options traders were not willing to pay as much premium for those options. meaning that they were expecting less volatility from the S&P 500 going forward. The relationship suggests that when the market is less volatile, market participants expect lower levels of volatility into the future. And on the other side of things, when the market is extremely volatile, the market expects higher levels of volatility into the future. Next, we'll explore how implied volatility represents the probabilities around a stock's price changes into the future. When you look at any option chain, you'll typically see that there's an implied volatility. number associated with that expiration cycle, and that implied volatility number is presented as a percentage figure. But what does that percentage figure actually represent? The first thing to know is that implied volatility is always expressed as an annualized percentage. So even if you're looking at 30-day option prices, the implied volatility number that you're looking at based on those 30-day option prices is annualized, meaning that they're taking the 30-day option prices and calculating implied volatility, but they're calculating implied volatility over a one-year period from those 30-day option prices. More specifically, the implied volatility percentage is the one standard deviation stock price range over the next year. In statistics, a one standard deviation range encompasses about 68% of potential outcomes around the mean or average. In the context of the stock market, the mean or average is the current stock price. The formula for the one-year one standard deviation range is the stock price plus the one standard deviation range. or minus the stock price times implied volatility. Let's go ahead and take a look at some examples so I can show you exactly what I mean by the one standard deviation range and how we get that range by using implied volatility and the current stock price. Based on the 374 Netflix price and a 39% implied volatility, the one year standard deviation range for Netflix is between $228.14 and $519. and 86 cents. Said another way, the market is pricing in a 68% probability that Netflix is somewhere within 39% of its current price or between $228 and 14 cents and $519 and 80 cents. cents one year from today. With Coca-Cola at $52 and an implied volatility of 20%, the one-year standard deviation range for Coca-Cola is between $41.60 and $62.40. Said another way, the market is pricing in a 68% probability that Coca-Cola is somewhere within 20% of its current price or between $41.60 and $62.40 one year from today. Let's go ahead and look at some charts to visualize implied volatility and the corresponding standard deviation ranges that we calculate from implied volatility. The first chart we're going to look at is a $100 stock with 25% implied volatility. In this chart, 68% of the area under the curve falls between the stock prices of $75 and $125, indicating that the market is implying a 68% probability that the stock price is between $75 and $125 one year from today. Now, it doesn't mean that the stock price will not trade beyond these prices, but it implies a low probability of occurring based on the market's level of uncertainty about that company. We can also calculate two and three standard deviation ranges by by multiplying the one standard deviation range by two and three, respectively. A $100 stock with 25% implied volatility has a one standard deviation range that extends $25 above and below the current stock price. Therefore, a $100 stock with 25% implied volatility has a two standard deviation range that extends $50 above and below the current stock price, as visualized in this chart. In statistics, a two standard deviation range encompasses about 95% of the outcomes around the mean or average, but in the case of the stock market, we're talking about the current stock price and we're calculating the standard deviation range around that current stock price. So in other words, a two standard deviation range means that the stock price has about a 95% chance of being within that two standard deviation range one year into the future. To visualize the differences between a high implied volatility and low implied volatility stock, let's go ahead and look at a visualization of two one- $100 stocks that are trading with different levels of implied volatility so we can visualize the stock price outcomes that are expected from those stocks going into the future. The 10% implied volatility scenario tells us that there's a much higher probability that the stock price will be somewhere between $85 and $115 as compared to the 25% implied volatility scenario. On the other hand, the 25% implied volatility scenario tells us that there's a much higher implied probability that the stock price is going to be somewhere between $85 and $115. is below $85 or above $115 in a year compared to the same $100 stock trading with 10% implied volatility. If we looked at both of these stocks and we compared their option prices, the stock with 25% implied volatility would have more expensive options than the same stock with 10% implied volatility. And we know that has to be true because implied volatility is derived from the stock's option prices. Given that we're comparing two similarly priced stocks and we're looking at options. with the same amount of time until they expire. For example, the 70 put or the 130 call would be nearly worthless on the 10% implied volatility stock because the implied probability of the stock trading beyond those levels is almost 0%. However, if we looked at the 70 put or the 130 call on the 25% implied volatility stock, we'd find that the options have some value because the stock price has a much wider range of expected price changes compared to the 10% implied volatility stock. And we know that has to be- to be true because the option prices are implying the expected amount of volatility from that stock in the future. In the simplest terms possible, implied volatility tells us how much uncertainty the market has for a particular stock going into the future. And since implied volatility is derived from a stock's option prices, we can then say that a stock's option prices tell us how much uncertainty the market has about that particular company. The next thing we're going to talk about is implied volatility rank and implied volatility percentile. These are two two implied volatility metrics that traders use to determine whether a stock's implied volatility is currently high or low relative to that stock's historical levels of implied volatility. By looking at a stock's implied volatility, it's not immediately clear whether that level of implied volatility is low or high. For example, if I look at a stock and it has 25% implied volatility and I look at another stock that has 50% implied volatility, how do I know where those implied volatility levels lie in the stock? in the terms of the historical level. of implied volatility that have been observed in each of those stocks. Just because that 50% implied volatility stock has higher levels of implied volatility, it doesn't necessarily mean that that 50% implied volatility is high. For instance, the 50% implied volatility could be low because that stock could normally trade with 65% implied volatility and in that scenario the 50% implied volatility would actually be pretty low relative to that stock's historical implied volatility readings. On the other hand, that 20% implied volatility stock could normally trade with 15% implied volatility, in which case that 20% implied volatility would actually be high relative to the normal 15% implied volatility that is normally observed in that stock. When it comes to determining whether a stock's implied volatility is currently high or low, traders turn to implied volatility rank and implied volatility percentile. Both are ways to measure a stock's current level of implied volatility against its past level. of implied volatility. Implied volatility rank, or IV rank for short, is a calculation that takes a stock's current level of implied volatility and compares it with the highest implied volatility and the lowest implied volatility that's been observed in that stock over the past year. The formula for IV rank is the current implied volatility minus the lowest implied volatility over the past year, divided by the highest implied volatility over the past year, minus the lowest implied volatility over the past year. For example, the IV rank for a 20% implied volatility stock with a one-year implied volatility range between 15% and 35% would be 20 minus 15 divided by 35 minus 15, and that gives us 5 over 20 or 0.25, which comes out to an IV rank of 25%. An IV rank of 0% indicates that the current implied volatility is the very bottom of the one-year range, and an IV rank of 100% indicates that that the current implied volatility is at the top of the one-year range. So for the stock to have an IV rank of 25%, it means that the current level of implied volatility is closer to the lower end of the implied volatility range that's been observed over the past year. The other implied volatility metric that traders use to measure implied volatility against itself is known as implied volatility percentile or IV percentile for short. Unlike IV rank, implied volatility percentile is frequency based, meaning that implied volatility is at the top of the one-year implied volatility percentile tells us how often a stock's implied volatility has been below the current level of implied volatility over the past year. For example, an IV percentile of 85% would mean that the stock's implied volatility has been below the current level of implied volatility 85% of the time over the past year. The formula for IV percentile is the number of trading days with implied volatility below the current implied volatility divided by 252. since there are 252 trading days in a year. As an example, let's say a stock's current implied volatility is 35% and on 180 of the past 252 trading days, the stock's implied volatility has been below 35%. In this case, the stock's 35% implied volatility gives us an implied volatility percentile equal to 180 over 252, which comes out to 0.7142 or an IV percentile. percentile of 71.42%. The stock's IV percentile is 71.4% because the implied volatility has been below the current reading of 35% on 71.4% of trading days over the past year. So now that we've talked about implied volatility rank and implied volatility percentile, which metric is better to use when determining whether a stock's implied volatility is currently high or low? Every trader has their preference, but in my opinion, one of the downfalls of implied volatility rank is that it does not tell you the frequency in which the stock's implied volatility was lower than the current level of implied volatility. Implied volatility rank simply tells us where a stock's current level of implied volatility falls within the one-year implied volatility range. One of the downfalls of IV rank is that after a period of abnormally high implied volatility, the implied volatility rank will come in at lower readings for almost all levels of implied volatility into the future, regardless of whether or not that level of implied volatility is actually still high or low. To demonstrate this to you, let's go ahead and look at a chart of the S&P 500 and the VIX index and look at IV rank through a period of abnormally high implied volatility as measured by the VIX index. After that abnormally high level of implied volatility, we're going to look at IV rank and see how it behaves after that implied volatility spike relative to how it behaved before that spike in implied volatility. If you focus your attention to the very first days in this chart, you'll notice that the S&P 500 is still high. and P500 implied volatility. was around 22.5%, which translated to an IV rank over 75%. However, later on in the year, implied volatility spiked to 40%. In the shaded region on the very right of the graph, you'll notice that the implied volatility rose to 25%, but IV rank was less than 50%. When IV falls after a massive surge in implied volatility, IV rank readings will be low, even when implied volatility of that stock is still relatively high. In this example, the implied volatility of the S&P 500 is below 20% almost the entire year, but after the significant spike in implied volatility, the subsequent IV of 25% translated to an IV rank less than 50% later in the year. Let's go ahead and look at that same exact time period and chart, but this time instead of looking at IV rank, we'll track IV percentile to see how IV percentile performs before and after the spike in implied volatility. As we can see here, you even after the spike in implied volatility to 40%, the rise in implied volatility to 25% at the end of the year translated to an IV percentile of 93%, indicating that implied volatility was below 25% on 93% of the trading days over the past year. When the implied volatility of the S&P 500 spiked to 40%, what would happen if it stayed at 40% for an extended period of time? IV rank would be pinned at 100%. telling you that the 40% IV is the highest implied volatility the S&P 500 has seen over the past year, but IV percentile would actually begin to fall as the 40% implied volatility becomes more normal. For this reason, I believe IV percentile is the better implied volatility measurement to make trading decisions with, as IV percentile is frequency based, while IV rank just tells you where the current implied volatility falls within the highest and lowest values of implied volatility, seen over the past year. In this section, we're going to talk about using implied volatility to calculate expected stock price ranges over any timeframe. It isn't always necessary to do so, and in most cases you probably won't need to use this, but to calculate a stock's expected price range over any timeframe, you can use the following formula. The formula for calculating a stock's expected price range over any timeframe is equal to the stock price multiplied by implied volatility multiplied by the square root of the calendar days to expiration divided by 365. For example, on a $250 stock with 15% implied volatility, the 30-day one standard deviation range would be $250 times 15% times the square root of 30 over 365. That gives us a 30-day one standard deviation range of plus or minus $10.75. meaning that the stock has an implied 68% probability of being within $10.75 of $250 30 days from now. If we wanted a one-day stock price range calculation, we can adjust the formula accordingly and take the stock price of $250, multiply it by the implied volatility of 15%, and multiply that by the square root of 1 over 365. That gives us a one-day, one standard deviation range of $10.75. plus or minus $1.96 around the current stock price of $250. When performing this type of calculation, it's important to use the implied volatility of the expiration cycle that's closest to your target time frame. For example, if you're trying to calculate a 55-day expected range, it would be better to use the 45-day expiration cycle's implied volatility as opposed to a 180-day expiration cycle's implied volatility. The last topic I want to discuss in this video is fairly important because it's a common misconception for beginner options traders. This topic is about implied volatility around earnings and the reason I want to talk about this topic is because when people get into options trading, including myself when I first started, a lot of people are familiar with the fact that implied volatility is observed to increase leading into a stock's earnings report and knowing that implied volatility typically rises into a stock's earnings report, Naturally, it becomes a question of whether or not you can take advantage of that increase in implied volatility to profit from an options trade. More specifically, can you buy options before a stock's earnings report and profit from the increase in implied volatility? Because an increase in implied volatility must mean that the stock's option prices are actually increasing. So if you bought options before a stock's implied volatility increase, you should have a profit in theory. In this section, I'm actually going to debunk this because that is a misconception that a lot of traders have. And in most cases, the option prices are actually not changing that much. And in some cases, implied volatility can be observed to increase while the option prices are actually increasing. decreasing. If you remember from earlier, I defined implied volatility as the extrinsic value that exists in a stock's options. relative to the time they have until expiration. The key part of that sentence is relative to the time they have until expiration. The reason implied volatility increases into a company's earnings report is because the options in the expiration cycle that expires immediately after the earnings report, those options typically do not decay as normal. And if they hold on to their value as expiration approaches, that means implied volatility is going to increase because if we hold option prices constant as they approach expiration, expiration, that is implying that the market is expecting higher levels of volatility relative to the amount of time until those options expire. To prove this to you, let's go ahead and look at some historical option prices on stocks that are approaching their earnings date. In the following table, we're looking at the prices of options on Tesla on the days leading up to their earnings date in April of 2019. On each day, I recorded the price of the $262.50 straddle, which was the at-the-money straddle on the first day that I started recording the prices. see, the straddle price actually decreased on both days leading up to the earnings date, yet the implied volatility reading of the earnings expiration cycle went from 104% to 125%. The reason implied volatility increased was because the options barely lost any value despite seeing very little stock price movement during the final days before the options expired. More specifically, implied volatility increased because the options did not decay at the rate that Theta would have suggested. In other words, if option prices do not decay as expected or as implied by option pricing models, implied volatility will increase because those options are actually getting more expensive relative to the time they have until expiration. If there was no upcoming earnings announcement, we would expect the at-the-money options to decay at a rapid rate on any stock. With a stock's earnings date approaching, market participants are expecting a big movement in either direction because the new information that comes out from that stock's earnings report has the potential to increase or decrease the value of that stock by a significant margin because the market's perception of that company's performance can change significantly in one earnings report. In this example we're looking at United Airlines options on the day before and the day of earnings in April of 2019. On Monday April 15th UAL closed at $84.52 and the 85 straddle expiring that week was trading for $4.63. Implied volatility of the weekly expiration cycle was 72%. The following day, UAL closed at $85.17 and the 85 straddles price was $4.57, which is 6 cents lower than the previous day. The implied volatility of the weekly cycle had increased from 72% to 85% despite seeing no change in the option prices. Again, the reason implied volatility increased is because the options went from 3 days to expiration to $10. to two days to expiration without any loss in value. The passage of time with no decrease in the option prices resulted in a higher implied volatility reading. Basically what I'm trying to say here is that the increase in implied volatility leading up to a stock's earnings report is not necessarily an opportunity to buy options because just because implied volatility is increasing, that does not mean that the option prices themselves are increasing. That's a wrap on this video on implied volatility. I really hope you enjoyed all the topics that I discussed here. And And don't feel discouraged if you don't understand everything that I've discussed here, because this is a pretty heavy topic. The more exposure to these topics that you get, I promise that it'll start to make more sense. I encourage you to take some of the things that I've said here and try and actually observe that in the real marketplace. So go ahead and look at two similarly priced stocks, compare their options, and then look at their implied volatility and understand why one stock has a higher level of implied volatility or a lower level of implied volatility. Also, I would encourage you to look at the stock market. encourage you to look at a stock's option prices as the earnings date is approaching and record whether or not there's actually any option price changes occurring and also look at the level of implied volatility to see what's happening there. Be sure to check the links down in the description for additional resources. If you have any questions or comments, please leave a comment down below and I'll get back to you as soon as I can. I'm Chris from Project Option and I will see you in the next video.

complex topic. In this video, I'm going to show you that it's not as complicated as it seems as implied volatility is pretty intuitive once you get the hang of it. So let's get started.

First and foremost, what exactly is implied volatility? In the simplest terms possible, implied volatility represents the amount of volatility that is generated by represents the market's expected magnitude for a stock's future price movements. Implied volatility stems from a stock's option prices, which are implying how much volatility is expected from that stock going into the future. Let's look at a couple of examples of some real option prices on stocks from historical dates so I can demonstrate to you exactly what I mean by the option prices implying future volatility in that stock. Consider the following option prices that I recorded from two similarly priced stocks, which at the time were Pepsi and U.N.P. In this table, we're looking at the call option and the put option that are slightly above and below the stock price at the time of recording their prices.

As we can see, Pepsi was at $102 and the $105 call was $0.80, while the $100 put was $1.17. At the time of recording these option prices, Pepsi's implied volatility in the 37-day expiration cycle was 16.4%. With U.N.P. at roughly the same price as Pepsi, we can see that the $105 call was $0.80.

$2.72 and the 100 put was $1.92. At the time of recording these option prices, UNP's implied volatility in the 37-day expiration cycle was 30.9%. So the first key concept that I want you to understand here is that implied volatility comes from a stock's option prices, and a common misconception, especially for beginner options traders, is that the option prices are coming from implied volatility. When we trade options, we're trading the option contracts themselves.

we're not trading the implied volatility number. By trading the option contracts, the option prices will change from day to day, and based on the changes in those option prices, based on the buying and selling pressure that's currently being observed in the marketplace, implied volatility is going to adjust according to those changes in the option prices. When comparing the Pepsi and UMP options, we can see that the higher UMP option prices, relative to the time until expiration, results in a higher implied volatility reading.

In other words, because we're comparing two similarly priced stocks and those stocks have different levels of implied volatility, by looking at the option prices we can figure out why those implied volatility levels are different. The higher UNP option prices tell us that the market is implying more expected stock price volatility compared to Pepsi because the options in Pepsi are cheaper than the options in UNP and both of the options have the same amount of time until expiration. But it's not the options overall price that gives us implied volatility, it's actually the extrinsic value that exists in the stock's options. In other words, implied volatility represents the amount of extrinsic value that exists in a stock's options relative to the time they have until they expire.

Let's look at some real-time examples and compare some similarly priced stocks looking at the options on each stock to determine which one has higher levels of implied volatility. To do this, I'm going to use the Tastyworks trading platform, so let's go ahead and hop onto the platform and look at some option prices. If you're unfamiliar with Tastyworks, be sure to check out the link in the description. description if you'd like to know more about their technology and their commission structure.

I've just opened up the Tastyworks trading platform and I'm gonna run through this very quickly to compare the option prices on two similarly priced stocks with the same amount of time until expiration. The two products I'm going to compare are SPY which is the S&P 500 ETF and then we're gonna look at Adobe because both of these stocks are right around $292. So to get started I'm gonna open up the September options with 49 days to expiration. and I'm going to look at the price of the 290 straddle. As we can see here on SPY, this straddle is trading for $15 and the extrinsic value is right around $1,310.

This is giving us an implied volatility of about 18%, but keep in mind it's not this particular straddle, but we're just going to compare the implied volatility. and the extrinsic value of these two straddles. So if I go to Adobe, open up the September options with 49 days to expiration, and I queue up the 290 short straddle, we can see that this straddle is trading for $27 and the extrinsic value that exists in this particular straddle is 2,500.

and with the increase in extrinsic value compared to SPY, we would expect Adobe to be trading with higher levels of implied volatility. If we look to the top right here, we can see that Adobe in the September expiration cycle, these options are giving us an implied volatility of 33.7%. When market participants trade options, they are either buying options or selling options.

When option buyers are willing to pay more for a stock's options and option sellers demand more premium for selling a stock's options, that's an indication that the market is anticipating lots of volatility from that stock price in the future. Conversely, when option buyers are not willing to pay as much for those options and option sellers will collect less... premium to sell those options, that's an indication that the market is not anticipating a lot of volatility from the stock price in the future. And we know that because the option buyers are paying less for the options, but more importantly, option sellers are willing to accept lower premiums for taking the risk by selling those options.

So this begs the question, what makes traders more or less willing to pay higher premiums for a stock's options? In other words, why do a stock's option prices experience wide price fluctuations and therefore big changes in implied? volatility from time to time.

Generally speaking, there's a very close relationship between a stock or product's recent volatility or historical volatility and the level of volatility that is expected into the future. And in other words, there's a close relationship between a stock's historical volatility or how volatile the stock has been in recent periods and the option prices on that stock. To prove this, I plotted the one month historical volatility of the S&P 500 against the levels of the VIX index after recording those levels of observed volatility. The VIX index measures one month option prices on the S&P 500 index, so by comparing the S&P 500's historical volatility to the VIX index, I can draw a conclusion as to whether or not historical volatility has any impact on the option prices on the S&P 500. And in other words, I'm trying to see if there's any relationship between the historical volatility of the S&P 500 and the future expected volatility of the S&P 500, which is implied through the option price.

prices on the S&P 500 index. As we can see, there's a very clear relationship between the S&P 500's historical volatility and the one month option prices as measured by the VIX index. When the recent volatility in the S&P 500 was at lower levels, so was the VIX index, implying that when the S&P 500 was not as volatile, the option prices were cheaper, meaning that when the S&P 500 was experiencing low levels of volatility, options traders were not willing to pay as much premium for those options. meaning that they were expecting less volatility from the S&P 500 going forward. The relationship suggests that when the market is less volatile, market participants expect lower levels of volatility into the future.

And on the other side of things, when the market is extremely volatile, the market expects higher levels of volatility into the future. Next, we'll explore how implied volatility represents the probabilities around a stock's price changes into the future. When you look at any option chain, you'll typically see that there's an implied volatility.

number associated with that expiration cycle, and that implied volatility number is presented as a percentage figure. But what does that percentage figure actually represent? The first thing to know is that implied volatility is always expressed as an annualized percentage.

So even if you're looking at 30-day option prices, the implied volatility number that you're looking at based on those 30-day option prices is annualized, meaning that they're taking the 30-day option prices and calculating implied volatility, but they're calculating implied volatility over a one-year period from those 30-day option prices. More specifically, the implied volatility percentage is the one standard deviation stock price range over the next year. In statistics, a one standard deviation range encompasses about 68% of potential outcomes around the mean or average. In the context of the stock market, the mean or average is the current stock price.

The formula for the one-year one standard deviation range is the stock price plus the one standard deviation range. or minus the stock price times implied volatility. Let's go ahead and take a look at some examples so I can show you exactly what I mean by the one standard deviation range and how we get that range by using implied volatility and the current stock price. Based on the 374 Netflix price and a 39% implied volatility, the one year standard deviation range for Netflix is between $228.14 and $519. and 86 cents.

Said another way, the market is pricing in a 68% probability that Netflix is somewhere within 39% of its current price or between $228 and 14 cents and $519 and 80 cents. cents one year from today. With Coca-Cola at $52 and an implied volatility of 20%, the one-year standard deviation range for Coca-Cola is between $41.60 and $62.40.

Said another way, the market is pricing in a 68% probability that Coca-Cola is somewhere within 20% of its current price or between $41.60 and $62.40 one year from today. Let's go ahead and look at some charts to visualize implied volatility and the corresponding standard deviation ranges that we calculate from implied volatility. The first chart we're going to look at is a $100 stock with 25% implied volatility. In this chart, 68% of the area under the curve falls between the stock prices of $75 and $125, indicating that the market is implying a 68% probability that the stock price is between $75 and $125 one year from today.

Now, it doesn't mean that the stock price will not trade beyond these prices, but it implies a low probability of occurring based on the market's level of uncertainty about that company. We can also calculate two and three standard deviation ranges by by multiplying the one standard deviation range by two and three, respectively. A $100 stock with 25% implied volatility has a one standard deviation range that extends $25 above and below the current stock price.

Therefore, a $100 stock with 25% implied volatility has a two standard deviation range that extends $50 above and below the current stock price, as visualized in this chart. In statistics, a two standard deviation range encompasses about 95% of the outcomes around the mean or average, but in the case of the stock market, we're talking about the current stock price and we're calculating the standard deviation range around that current stock price. So in other words, a two standard deviation range means that the stock price has about a 95% chance of being within that two standard deviation range one year into the future.

To visualize the differences between a high implied volatility and low implied volatility stock, let's go ahead and look at a visualization of two one- $100 stocks that are trading with different levels of implied volatility so we can visualize the stock price outcomes that are expected from those stocks going into the future. The 10% implied volatility scenario tells us that there's a much higher probability that the stock price will be somewhere between $85 and $115 as compared to the 25% implied volatility scenario. On the other hand, the 25% implied volatility scenario tells us that there's a much higher implied probability that the stock price is going to be somewhere between $85 and $115. is below $85 or above $115 in a year compared to the same $100 stock trading with 10% implied volatility.

If we looked at both of these stocks and we compared their option prices, the stock with 25% implied volatility would have more expensive options than the same stock with 10% implied volatility. And we know that has to be true because implied volatility is derived from the stock's option prices. Given that we're comparing two similarly priced stocks and we're looking at options. with the same amount of time until they expire.

For example, the 70 put or the 130 call would be nearly worthless on the 10% implied volatility stock because the implied probability of the stock trading beyond those levels is almost 0%. However, if we looked at the 70 put or the 130 call on the 25% implied volatility stock, we'd find that the options have some value because the stock price has a much wider range of expected price changes compared to the 10% implied volatility stock. And we know that has to be- to be true because the option prices are implying the expected amount of volatility from that stock in the future.

In the simplest terms possible, implied volatility tells us how much uncertainty the market has for a particular stock going into the future. And since implied volatility is derived from a stock's option prices, we can then say that a stock's option prices tell us how much uncertainty the market has about that particular company. The next thing we're going to talk about is implied volatility rank and implied volatility percentile.

These are two two implied volatility metrics that traders use to determine whether a stock's implied volatility is currently high or low relative to that stock's historical levels of implied volatility. By looking at a stock's implied volatility, it's not immediately clear whether that level of implied volatility is low or high. For example, if I look at a stock and it has 25% implied volatility and I look at another stock that has 50% implied volatility, how do I know where those implied volatility levels lie in the stock? in the terms of the historical level.

of implied volatility that have been observed in each of those stocks. Just because that 50% implied volatility stock has higher levels of implied volatility, it doesn't necessarily mean that that 50% implied volatility is high. For instance, the 50% implied volatility could be low because that stock could normally trade with 65% implied volatility and in that scenario the 50% implied volatility would actually be pretty low relative to that stock's historical implied volatility readings. On the other hand, that 20% implied volatility stock could normally trade with 15% implied volatility, in which case that 20% implied volatility would actually be high relative to the normal 15% implied volatility that is normally observed in that stock. When it comes to determining whether a stock's implied volatility is currently high or low, traders turn to implied volatility rank and implied volatility percentile.

Both are ways to measure a stock's current level of implied volatility against its past level. of implied volatility. Implied volatility rank, or IV rank for short, is a calculation that takes a stock's current level of implied volatility and compares it with the highest implied volatility and the lowest implied volatility that's been observed in that stock over the past year. The formula for IV rank is the current implied volatility minus the lowest implied volatility over the past year, divided by the highest implied volatility over the past year, minus the lowest implied volatility over the past year.

For example, the IV rank for a 20% implied volatility stock with a one-year implied volatility range between 15% and 35% would be 20 minus 15 divided by 35 minus 15, and that gives us 5 over 20 or 0.25, which comes out to an IV rank of 25%. An IV rank of 0% indicates that the current implied volatility is the very bottom of the one-year range, and an IV rank of 100% indicates that that the current implied volatility is at the top of the one-year range. So for the stock to have an IV rank of 25%, it means that the current level of implied volatility is closer to the lower end of the implied volatility range that's been observed over the past year.

The other implied volatility metric that traders use to measure implied volatility against itself is known as implied volatility percentile or IV percentile for short. Unlike IV rank, implied volatility percentile is frequency based, meaning that implied volatility is at the top of the one-year implied volatility percentile tells us how often a stock's implied volatility has been below the current level of implied volatility over the past year. For example, an IV percentile of 85% would mean that the stock's implied volatility has been below the current level of implied volatility 85% of the time over the past year. The formula for IV percentile is the number of trading days with implied volatility below the current implied volatility divided by 252. since there are 252 trading days in a year. As an example, let's say a stock's current implied volatility is 35% and on 180 of the past 252 trading days, the stock's implied volatility has been below 35%.

In this case, the stock's 35% implied volatility gives us an implied volatility percentile equal to 180 over 252, which comes out to 0.7142 or an IV percentile. percentile of 71.42%. The stock's IV percentile is 71.4% because the implied volatility has been below the current reading of 35% on 71.4% of trading days over the past year.

So now that we've talked about implied volatility rank and implied volatility percentile, which metric is better to use when determining whether a stock's implied volatility is currently high or low? Every trader has their preference, but in my opinion, one of the downfalls of implied volatility rank is that it does not tell you the frequency in which the stock's implied volatility was lower than the current level of implied volatility. Implied volatility rank simply tells us where a stock's current level of implied volatility falls within the one-year implied volatility range. One of the downfalls of IV rank is that after a period of abnormally high implied volatility, the implied volatility rank will come in at lower readings for almost all levels of implied volatility into the future, regardless of whether or not that level of implied volatility is actually still high or low.

To demonstrate this to you, let's go ahead and look at a chart of the S&P 500 and the VIX index and look at IV rank through a period of abnormally high implied volatility as measured by the VIX index. After that abnormally high level of implied volatility, we're going to look at IV rank and see how it behaves after that implied volatility spike relative to how it behaved before that spike in implied volatility. If you focus your attention to the very first days in this chart, you'll notice that the S&P 500 is still high.

and P500 implied volatility. was around 22.5%, which translated to an IV rank over 75%. However, later on in the year, implied volatility spiked to 40%. In the shaded region on the very right of the graph, you'll notice that the implied volatility rose to 25%, but IV rank was less than 50%.

When IV falls after a massive surge in implied volatility, IV rank readings will be low, even when implied volatility of that stock is still relatively high. In this example, the implied volatility of the S&P 500 is below 20% almost the entire year, but after the significant spike in implied volatility, the subsequent IV of 25% translated to an IV rank less than 50% later in the year. Let's go ahead and look at that same exact time period and chart, but this time instead of looking at IV rank, we'll track IV percentile to see how IV percentile performs before and after the spike in implied volatility.

As we can see here, you even after the spike in implied volatility to 40%, the rise in implied volatility to 25% at the end of the year translated to an IV percentile of 93%, indicating that implied volatility was below 25% on 93% of the trading days over the past year. When the implied volatility of the S&P 500 spiked to 40%, what would happen if it stayed at 40% for an extended period of time? IV rank would be pinned at 100%.

telling you that the 40% IV is the highest implied volatility the S&P 500 has seen over the past year, but IV percentile would actually begin to fall as the 40% implied volatility becomes more normal. For this reason, I believe IV percentile is the better implied volatility measurement to make trading decisions with, as IV percentile is frequency based, while IV rank just tells you where the current implied volatility falls within the highest and lowest values of implied volatility, seen over the past year. In this section, we're going to talk about using implied volatility to calculate expected stock price ranges over any timeframe. It isn't always necessary to do so, and in most cases you probably won't need to use this, but to calculate a stock's expected price range over any timeframe, you can use the following formula.

The formula for calculating a stock's expected price range over any timeframe is equal to the stock price multiplied by implied volatility multiplied by the square root of the calendar days to expiration divided by 365. For example, on a $250 stock with 15% implied volatility, the 30-day one standard deviation range would be $250 times 15% times the square root of 30 over 365. That gives us a 30-day one standard deviation range of plus or minus $10.75. meaning that the stock has an implied 68% probability of being within $10.75 of $250 30 days from now. If we wanted a one-day stock price range calculation, we can adjust the formula accordingly and take the stock price of $250, multiply it by the implied volatility of 15%, and multiply that by the square root of 1 over 365. That gives us a one-day, one standard deviation range of $10.75. plus or minus $1.96 around the current stock price of $250. When performing this type of calculation, it's important to use the implied volatility of the expiration cycle that's closest to your target time frame.

For example, if you're trying to calculate a 55-day expected range, it would be better to use the 45-day expiration cycle's implied volatility as opposed to a 180-day expiration cycle's implied volatility. The last topic I want to discuss in this video is fairly important because it's a common misconception for beginner options traders. This topic is about implied volatility around earnings and the reason I want to talk about this topic is because when people get into options trading, including myself when I first started, a lot of people are familiar with the fact that implied volatility is observed to increase leading into a stock's earnings report and knowing that implied volatility typically rises into a stock's earnings report, Naturally, it becomes a question of whether or not you can take advantage of that increase in implied volatility to profit from an options trade. More specifically, can you buy options before a stock's earnings report and profit from the increase in implied volatility? Because an increase in implied volatility must mean that the stock's option prices are actually increasing.

So if you bought options before a stock's implied volatility increase, you should have a profit in theory. In this section, I'm actually going to debunk this because that is a misconception that a lot of traders have. And in most cases, the option prices are actually not changing that much.

And in some cases, implied volatility can be observed to increase while the option prices are actually increasing. decreasing. If you remember from earlier, I defined implied volatility as the extrinsic value that exists in a stock's options. relative to the time they have until expiration.

The key part of that sentence is relative to the time they have until expiration. The reason implied volatility increases into a company's earnings report is because the options in the expiration cycle that expires immediately after the earnings report, those options typically do not decay as normal. And if they hold on to their value as expiration approaches, that means implied volatility is going to increase because if we hold option prices constant as they approach expiration, expiration, that is implying that the market is expecting higher levels of volatility relative to the amount of time until those options expire. To prove this to you, let's go ahead and look at some historical option prices on stocks that are approaching their earnings date. In the following table, we're looking at the prices of options on Tesla on the days leading up to their earnings date in April of 2019. On each day, I recorded the price of the $262.50 straddle, which was the at-the-money straddle on the first day that I started recording the prices.

see, the straddle price actually decreased on both days leading up to the earnings date, yet the implied volatility reading of the earnings expiration cycle went from 104% to 125%. The reason implied volatility increased was because the options barely lost any value despite seeing very little stock price movement during the final days before the options expired. More specifically, implied volatility increased because the options did not decay at the rate that Theta would have suggested.

In other words, if option prices do not decay as expected or as implied by option pricing models, implied volatility will increase because those options are actually getting more expensive relative to the time they have until expiration. If there was no upcoming earnings announcement, we would expect the at-the-money options to decay at a rapid rate on any stock. With a stock's earnings date approaching, market participants are expecting a big movement in either direction because the new information that comes out from that stock's earnings report has the potential to increase or decrease the value of that stock by a significant margin because the market's perception of that company's performance can change significantly in one earnings report. In this example we're looking at United Airlines options on the day before and the day of earnings in April of 2019. On Monday April 15th UAL closed at $84.52 and the 85 straddle expiring that week was trading for $4.63. Implied volatility of the weekly expiration cycle was 72%.

The following day, UAL closed at $85.17 and the 85 straddles price was $4.57, which is 6 cents lower than the previous day. The implied volatility of the weekly cycle had increased from 72% to 85% despite seeing no change in the option prices. Again, the reason implied volatility increased is because the options went from 3 days to expiration to $10.

to two days to expiration without any loss in value. The passage of time with no decrease in the option prices resulted in a higher implied volatility reading. Basically what I'm trying to say here is that the increase in implied volatility leading up to a stock's earnings report is not necessarily an opportunity to buy options because just because implied volatility is increasing, that does not mean that the option prices themselves are increasing. That's a wrap on this video on implied volatility.

I really hope you enjoyed all the topics that I discussed here. And And don't feel discouraged if you don't understand everything that I've discussed here, because this is a pretty heavy topic. The more exposure to these topics that you get, I promise that it'll start to make more sense.

I encourage you to take some of the things that I've said here and try and actually observe that in the real marketplace. So go ahead and look at two similarly priced stocks, compare their options, and then look at their implied volatility and understand why one stock has a higher level of implied volatility or a lower level of implied volatility. Also, I would encourage you to look at the stock market. encourage you to look at a stock's option prices as the earnings date is approaching and record whether or not there's actually any option price changes occurring and also look at the level of implied volatility to see what's happening there. Be sure to check the links down in the description for additional resources.

If you have any questions or comments, please leave a comment down below and I'll get back to you as soon as I can. I'm Chris from Project Option and I will see you in the next video.

Transcript for:Understanding Implied Volatility in Options

Transcript for:
Understanding Implied Volatility in Options