What Do CBOE Volatility Indexes Say?

The CBOE publishes several options implied volatility indexes that can be helpful to stock investors who want to peek around the corner to the future through the eyes of options traders.

These two tables show the options implied (30-day future) volatility for several important indexes or index funds:

click image to enlarge

The “per year” column is the published annualized volatility (1 standard deviation). The columns for other periods (quarter, month, week and day) are math transforms of the annualized volatility to show the expected volatility for those periods of time.

Plus or minus one standard deviation is expected to encompass 67% of prices during the period. Plus or minus two standard deviations is expected to encompass 95% of prices during the period.

Example: The “per day” column says that the price of a GLD position is expected to move within a plus or minus one-day 1.09% variation with a 67% probability, and to move within a plus or minus one-day 2.19% variation with a 95% probability.

This sort of information can be useful in selecting securities based on volatility and also in setting stop loss parameters.

The proxy securities for the indexes in the tables are DIA (DJIA 30), SPY (S&P 500), QQQQ (NASDAQ 100), and IWM (Russell 2000). Oil, gold and the Euro volatility indexes are based directly on the underlying ETFs: USO, GLD and FXE.

Disclosure: We own SPY, IWM, GLD and FXE in some portfolios.

Comments

[Freya:]

So, what Do the CBOE Volatility Indexes Say?

Wil there be a part 2 to this article?

Oct 20 01:58 AM

[Richard Shaw:]

FREYA - The CBOE publishes options implied volatility indexes and expresses the volatility as an annualized figure . The table we produced transforms that annual data into it's one-day, one-week, one-month and one-quarter equivalents (not a linear transformation - something most people can't do unless they remember the math from a statistic course). That more granular data is what the CBOE indexes "say".

Use of what they "say" is dependent on what kind of investing you are doing and what issues are on your mind.

That data which is not published by the CBOE can be useful to investors concerned about the volatility of the underlying indexes or funds over those shorter periods of time.

As the article says, that information can be useful when thinking about setting up stop loss orders. You need to be aware of the expected level of volatility to know where the noise level in price action will be as you decide how to set stop loss order parameters.

No, there is not a specific Part 2 planned or needed for this article, although we will likely write more about volatility which has been our theme in the last few articles.

Oct 20 09:58 AM

[Nate Whalen:]

Is there any way to calculate the tables on our own or a place we can refer to for updates? It would be extremely helpful. Exactly what figures are the volatility data calculated from?

On Oct 20 09:58 AM Richard Shaw wrote:

> FREYA - The CBOE publishes options implied volatility indexes and
> expresses the volatility as an annualized figure . The table we
> produced transforms that annual data into it's one-day, one-week,
> one-month and one-quarter equivalents (not a linear transformation
> - something most people can't do unless they remember the math from
> a statistic course). That more granular data is what the CBOE indexes
> "say".
>
> Use of what they "say" is dependent on what kind of investing you
> are doing and what issues are on your mind.
>
> That data which is not published by the CBOE can be useful to investors
> concerned about the volatility of the underlying indexes or funds
> over those shorter periods of time.
>
> As the article says, that information can be useful when thinking
> about setting up stop loss orders. You need to be aware of the expected
> level of volatility to know where the noise level in price action
> will be as you decide how to set stop loss order parameters.
>
> No, there is not a specific Part 2 planned or needed for this article,
> although we will likely write more about volatility which has been
> our theme in the last few articles.

Oct 20 02:30 PM

[Richard Shaw:]

Nate:

The CBOE volatility index values are calculated by the CBOE based on the implied volatility of the near Put and Call options that have strike prices close to the market price of the underlying index or security. The CBOE provides a detailed white paper on the derivation of the VIX:
cboe.com/micro/VIX/vix...

You can obtain the annual options implied volatility from several sources, including the CBOE:
www.cboe.com/DelayedQu...

For securities or indexes other than the few tracked by CBOE for volatility, you must rely on historical volatility which can be calculated using Excel from data such as that provided by free vendors such as Yahoo, and for a larger spectrum through subscription vendors such a MetaStock from Reuters. Recent historical volatility and options implied volatility are often fairly close.

The logic of volatility and probability is based on the assumption of a near normal distribution of the natural log values of price changes. The volatility figure represents one standard deviation.

The math to transform volatility for one period of time to another is simple. To create volatility for a period less than one year from annual data, multiply the annual value by the square root of the fraction of a year. Example: the quarterly volatility is equal to the annual volatility times the square root of 1/4, and the weekly value is the annual value times the square root of 1/52.

Oct 20 03:07 PM

[Baboon:]

My understanding is that once someone understands the volatility and normal distribution he is unwilling to use the stop losses.


On Oct 20 09:58 AM Richard Shaw wrote:

> FREYA - The CBOE publishes options implied volatility indexes and
> expresses the volatility as an annualized figure . The table we
> produced transforms that annual data into it's one-day, one-week,
> one-month and one-quarter equivalents (not a linear transformation
> - something most people can't do unless they remember the math from
> a statistic course). That more granular data is what the CBOE indexes
> "say".
>
> Use of what they "say" is dependent on what kind of investing you
> are doing and what issues are on your mind.
>
> That data which is not published by the CBOE can be useful to investors
> concerned about the volatility of the underlying indexes or funds
> over those shorter periods of time.
>
> As the article says, that information can be useful when thinking
> about setting up stop loss orders. You need to be aware of the expected
> level of volatility to know where the noise level in price action
> will be as you decide how to set stop loss order parameters.
>
> No, there is not a specific Part 2 planned or needed for this article,
> although we will likely write more about volatility which has been
> our theme in the last few articles.

Oct 21 02:58 PM

[Richard Shaw:]

Baboon: Please elaborate.

Oct 21 03:01 PM

[Baboon:]

How would someone determine under normal distribution what is correct direction of the market? In other words how one can guess whether the market will go higher or lower under normal distribution? Since that's what happens when a person decides to place a stop loss: he admits that he placed a wrong bet on the market direction. And that I believe is impossible under normal distribution.


On Oct 21 03:01 PM Richard Shaw wrote:

> Baboon: Please elaborate.

Oct 21 04:13 PM

[Richard Shaw:]

Baboon:
The normal distribution is only an approximation to get approximate boundaries for probable behavior. In no way do we believe that the market is random. In fact, the market is demonstrated by observation to be skewed in an upward direction.

The normal distribution is imperfect as is any conceptualization. The trends lend ideas as to direction within the probability range.

By stopping losses and not stopping gains the skew to the upside is increased.

It is not correct to say that using stops is an admission of having made a wrong decision. At the very least trailing stops prevent negative outliers from devastating a portfolio while allowing the long investor to benefit from positive outliers.

But then we all place our bets and take our chances based on how we view the world. That's how we view it and so far we make money and sleep better at night knowing outliers will not sink us.

Thanks for commenting.

Oct 21 04:35 PM