Two critical concepts to be familiar within the options trading realm are *volatility* and *mean reversion.*

As it relates to equity derivatives, volatility can be defined as a measurement of how much the price of a financial instrument fluctuates over time - in this case, a stock (or underlying).

It's important to understand that the ultimate value of an option with a particular strike price and duration (time until expiration) is based on where the underlying stock price is likely to settle at expiration.

Options are of course priced in dollars and cents, but that value can be translated into a volatility "price," and vice versa.

For example, if XYZ stock is trading $100/share, and the stock has been trading in a tight range between $80 and $120 over the last 52 weeks, then short duration options with strike prices above $120 and below $80 will likely possess lower time premiums than options of stocks which fluctuate in price to a much higher degree.

Of course stock XYZ is subject to broader market risk (i.e. a market crash) and idiosyncratic risk (i.e. stock specific risk such as litigation) which could quickly push the stock outside those limits.

The fact that XYZ has traded in a somewhat predictable range (in this example) would therefore affect market participants' perception that strikes outside that level could finish in the money.

The *volatility* concept, as it relates to options trading, can actually be broken down into three distinct categories:

**historical volatility****implied volatility****future volatility**

*Historical volatility* is the easiest to understand of the three terms listed above as it is observable. Every stock has a specific opening and closing price for each day it has traded. Therefore, a data scientist can compute the exact historical volatility (movement) of a stock over a defined period of time in history.

*Implied volatility *is the market price for volatility. One can look at the bid/ask of a particular option (symbol, strike, and duration) and observe at what price trades are being executed. This value represents the current market price for volatility in an option, often called implied volatility.

Of the three terms listed above, *future volatility* is of course the most difficult to understand.

Future volatility is the holy grail of options trading. Such a value involves estimating the future value of a stock, which is of course unknown. Hedge funds, banks, proprietary trading firms and the countless quantitative minds within them have spent innumerable sums of money trying to accurately (and consistently) forecast future volatility.

Obviously, the market players that most effectively estimate future volatility are likely some of the most profitable. However, as paradigm shifts can occur abruptly, there's no telling how long those forecasts will be effective and over what time horizon.

It's for precisely this reason that *mean reversion* is such an important concept in options trading - especially for those of us without the resources to build comprehensive volatility forecasting tools.

In finance,* mean reversion* is the assumption that a financial instrument's price will tend to move to the average price over time. If we apply that definition to the "price" of volatility, then it is the assumption that an option's volatility price will tend to move toward its average over time.

Consequently, a mean reversion trade expresses the thesis that an asset has deviated too far from its real value – or at least from its mean price – and that opportunities for profit exist when reversion to the mean occurs.

For example, if the one year historical volatility of stock XYZ is 20, and implied volatility (market volatility) for options with a one year duration is priced at 30, an opportunity theoretically exists to sell that option with the expectation that actual volatility in the underlying over a one year period will be less than 30.

By no means does this signify profit in such a trade is 100% assured because future volatility is unknown. However, it has been observed that options prices are mean reverting on average over time.

On the tastytrade network, we often leverage Implied Volatility Rank, or IVR, to help identify these opportunities.

Implied Volatility Rank (IVR) tells us whether implied volatility is high or low in a specific underlying based on the past year of implied volatility data. For example, if XYZ has had an implied volatility between 30 and 60 over the past year and implied volatility is currently at 45, XYZ would have an IVR of 50%.

Volatility expansion or contraction refers to implied volatility reverting to the mean.

When IVR is high (above 50%), we can expect a contraction. When IVR is low (below 50%), we can expect an expansion. Looking at IVR is a best practice at tastytrade because it provides context to the implied volatility of an underlying (stock).

IVR helps us decide whether to use a credit or debit strategy. While other considerations need to be taken into account, an IVR above 50% might be indicative of good options selling opportunities, while an IVR below 50% might be indicative of buying opportunities - both due to the mean reverting nature of volatility.

If you would like to explore these topics further, we encourage you to leverage the learn page on the tastytrade homepage or by leveraging the search engine on the website.

Please don’t hesitate to contact us with any questions or feedback at support@tastytrade.com.

Using different products to hedge positional risk is an advanced concept in equity options trading. If you’re interested in learning more about cross-product hedging, you’ve come to the right place!