Clues from the Options Market

By Brad Zigler

Many investors dismiss options trading as too arcane or speculative. While I can't say I blame them for thinking the business is mind-boggling, what with its use of Greek alphabetics like delta and gamma, it's not always about speculation. In fact, options are often used to reduce the risk of holding investment positions. Options are, in this sense, a form of insurance.

There's more than just a casual conceptual connection between options and insurance. In fact, your home and auto insurance policies are priced in the same manner as option market makers set their premiums.

Can't see the connection? Just think about the similarities between options and insurance:

• Term - Each contract provides a benefit to the holder only for a specified time period;
• Strike Price - A home or auto policy effectively grants the owner the right to "put" the subject property to the insurer at a specific price in the event of a total loss, just as a put option affords its holder the right to sell the underlying asset to the grantor at a predetermined exercise price;
• Premium - To obtain each contract's benefits, the holder must pay a risk-based fee to the seller.

It's setting that risk-based premium that involves all "the Greeks," as those parameters are known on the trading floor. Among the most important of the first-order metrics is vega (which, oddly enough, isn't a Greek letter at all). Vega is a measure of volatility, representing the dollar-per-shift in an option's value, as expected for each 1 percent change in the underlying asset's variance.

Too arcane? Let's look at a practical example to clarify things.

Right now, with the underlying Market Vectors Agribusiness Fund (NYSE Arca: MOO) trading at $39.42, November $40 calls are offered at $1.40 per share. If you dissect the premium with an options pricing model, you'd find embedded in that offer an assumption of annualized volatility—otherwise known as implied volatility—of 32.5 percent. Simply put, that's the degree to which the fund's share prices are expected to vary around their mean over the call's remaining life.

This volatility assumption translates to a vega coefficient of 0.05, which means that, holding everything else constant, you'd expect the call premium to increase by a nickel a share if the fund's price volatility increases by 1 percent (and to likewise decrease $0.05 if the volatility drops the same amount).

So if the market maker expects the standard deviation in MOO's daily returns to be 33.5 percent, you'd likely see the offer raised to $1.45 a share. Conversely, an expected risk of 31.5 percent would engender a $1.35 asking price.

At this point, you may be saying to yourself, "So what? I don't want to trade options." Well, that may indeed be the case, but it doesn't mean you can't make some friends in the options market. Sometimes, market makers can be a stock or fund trader's best buddy.

To fully appreciate this camaraderie, you need to make a distinction between implied volatility and historic, or statistical, volatility.

As explained above, implied volatility is the expected price variance in the underlying asset, but historic volatility is the actual price variance of the option's underlying asset over a given period of time—say, 20, 50 or 100 days. If we're analyzing the November options, which expire in 39 days, we're most interested in the 50-day historic volatility of MOO, since the option's life would fit within the statistic's span.

If you've got access to options pricing software and Excel spreadsheets, you can compare historic volatility vs. implied in option premiums, and pinpoint the market maker's risk expectations. Generally speaking, if there is enough trading interest in a given option that's close to the money—that is, one with an exercise price close to the underlying asset's current market price—implied volatility should be fairly close to historic volatility. Significant variance between the two metrics signals a seminal shift in risk perceptions or some market inefficiency.

If the November $40 MOO calls, for example, were priced with a 50 percent expected volatility (today, that'd be $2.31 a share), while historic volatility clocked in at only 32.5 percent, you probably ought to prepare yourself for wider price swings. That might mean tightening your money management stops on your open positions.

Conversely, if the options are priced with an implied volatility of only 20 percent, you might think twice about taking a position in the underlying asset. Either the market is underestimating the upcoming price volatility, or there's an earnest anticipation of a relatively quiet market for the option's tenure.

This is especially important in bullish markets, because standard deviations—i.e., volatilities—historically fall as prices rise. Volatility increases in bear markets.

So how do you determine these risk parameters? It's easy, really.

If you're acquainted with Excel spreadsheet protocols, you can derive an annualized historic volatility for any time period by keeping track of the day-by-day changes in the underlying asset's price. Then, using the argument "=STDEV(RANGE OF CELLS CONTAINING DAILY PRICE CHANGES, i.e., "B3:B157") *SQRT(252)" at the end of your data string will calculate your volatility factor. (Another option: You can obtain historic volatilities for 20-, 50-, and 100-day ranges on a wide spectrum of futures, stocks and other exchange-traded products at the Option Strategist.)

To derive implied volatilities, the Options Industry Council's online pricing calculator is your best bet. It's free and comes with lots of educational support.

With just a little effort, you can get the options market makers to offer up their insights on your favorite stock or fund. The best part is that you don't have to be on their turf. You can pick these clues up online at your leisure.

Comments

[Twitcher:]

Many thanks, Brad, for a good lesson.

Oct 15 02:39 PM

[jimmy46:]

Interesting and well written,
now what stocks have you screened and found changing volatility?

I know beta is the product of 2 numbers, so it's a bit flaky,
but to what extent is there a relationship between beta and
implied volatility?

Oct 15 04:22 PM

[SeekingTruth:]

Well Done Brad, and another rock solid fundamental article by you, and it's in a category I like very much.
I'm already a member at the OIC, and I'll check out the Option Strategist soon.
Articles like this are why I check in at SA.

No doubt the Bulls are in charge right now, but I wouldn't be surprised to see the market stall out and pull sideways for awhile after another couple of hundred DJ points or so on the upside. If this happens , it will be a tough environment for doing well in options. Possibly buying puts on high beta junk buoyed up by the strong rally may be a possibility. Any ideas in your future articles will be much appreciated.

Oct 15 07:28 PM

[Brad Zigler:]

Jimmy -

Beta is actually the QUOTIENT of two values: variance and covariance and represents a RELATIVE volatility (versus a market benchmark or index); implied volatility is an independent variable.


On Oct 15 04:22 PM jimmy46 wrote:

> Interesting and well written,
> now what stocks have you screened and found changing volatility?
>
>
> I know beta is the product of 2 numbers, so it's a bit flaky,
> but to what extent is there a relationship between beta and
> implied volatility?

Oct 16 12:42 AM

[JG Savoldi:]

Well done but possibly a bit complex for the average investor.

We'd offer a more simple approach that might be worth thinking about.

If the US stock market is going to continue tracking the BAM Model into the end of 2009/Q1 2010, (50% crash to SPX 529) the idea of selling covered calls would be a winning strategy.

The US stock market is more extended and more dangerous in our work than it was when we triggered sell signals into the 2007 TOP.

Possibly the biggest 'tell' here is in hearing acquaintances rationalize hanging onto stocks here even though they swore back in March to dump everything if the "market" could just bounce back to 10,000...

Oct 16 08:20 AM

[SeekingTruth:]

Brad, thanks for the added detail on Beta. Is this the same standard Beta used for stocks,etc , or is it a special Beta used for options?
I am well familiar with "standard" Beta for stocks and that it includes both randomness and standard deviation although I don't remember the exact formula.
Stocks have an improved metric called Correlation Coefficient which takes out much of the randomness and provides a truer "in - phase" component for comparing two fluctuating entities.
This is what my distant memory serves up (shaky) but any expansion or clarifications (a refresher) by you in your future articles will be greatly appreciated.
This kind of info by/from you is much more valuable than it appears on the surface , and I am encouraged and pleased by this line of investigation and discussion.
Please continue it! Thanks again.

Oct 16 10:09 AM

[Brad Zigler:]

Jimmy -

Beta can be computed against ANY benchmark. Most typically, the bogey in money management circles is the S&P 500 (SPX), but that's not necessarily the best yardstick to measure performance for ALLinvestments.

The same caveat applies to correlation. It's one thing to say that a large-cap, blue-chip fund correlates well to the SPX. The degree of fit between SPX and a small-cap portfolio expressed by correlation, however, bespeaks more of differences than similarities.


On Oct 16 10:09 AM SeekingTruth wrote:

> Brad, thanks for the added detail on Beta. Is this the same standard
> Beta used for stocks,etc , or is it a special Beta used for options?
>
> I am well familiar with "standard" Beta for stocks and that it includes
> both randomness and standard deviation although I don't remember
> the exact formula.
> Stocks have an improved metric called Correlation Coefficient which
> takes out much of the randomness and provides a truer "in - phase"
> component for comparing two fluctuating entities.
> This is what my distant memory serves up (shaky) but any expansion
> or clarifications (a refresher) by you in your future articles will
> be greatly appreciated.
> This kind of info by/from you is much more valuable than it appears
> on the surface , and I am encouraged and pleased by this line of
> investigation and discussion.
> Please continue it! Thanks again.

Oct 16 12:19 PM

[bobbybutte:]

Very good article

Last year when bud was taken over by Im bev the options market made it is very clear 4 months ahead of time

Oct 16 03:04 PM

[specguy:]

Brad,
Thanks for your clear explanation on Vega and its importance to option pricing and strategy. In your piece you state:

" Vega is a measure of volatility, representing the dollar-per-shift in an option's value, as expected for each 1 percent change in the underlying asset's variance."

Did you mean 'std. deviation' (the square root of variance) instead of "variance" in the above statement? I say this as you use the term "std. dev." 3 paragraphs below the above-cited quote as the parameter that a market maker would look to for valuing the option under consideration. You also use "variance" in other places in your article where I wonder if another word might be more precise.

Thanks again for presenting the concept so well.

Oct 16 03:47 PM

[Brad Zigler:]

Yes; "variance" in this context was used generically and was not meant to allude to the statistical metric.


On Oct 16 03:47 PM specguy wrote:

> Brad,
> Thanks for your clear explanation on Vega and its importance to option
> pricing and strategy. In your piece you state:
>
> " Vega is a measure of volatility, representing the dollar-per-shift
> in an option's value, as expected for each 1 percent change in the
> underlying asset's variance."
>
> Did you mean 'std. deviation' (the square root of variance) instead
> of "variance" in the above statement? I say this as you use the term
> "std. dev." 3 paragraphs below the above-cited quote as the parameter
> that a market maker would look to for valuing the option under consideration.
> You also use "variance" in other places in your article where I wonder
> if another word might be more precise.
>
> Thanks again for presenting the concept so well.

Oct 16 06:36 PM