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Covered-Calls 101

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Option Pricing - Volatility

A successful trader will always seek to improve the risk versus reward characteristics of his portfolio by looking for positions with the greatest possible margin for error. In order to achieve this objective, he must be able to accurately assess an option's value and one of the key components in the equation is the volatility of the underlying instrument.

Volatility can be described in many ways but with options, it is basically a measure of the range the underlying security has moved in the past or is expected to move over a given period of time. As a general rule, the more volatile the stock, the more costly the option, however there are different kinds of volatility and having a fundamental understanding of each type can help a trader determine if an option is cheap or expensive.

Statistical (SV) and Implied (IV) Volatility

Statistical (or historical) volatility is based on past values and it simply reflects how far an issue has deviated from its average (mean) price, normally on a daily basis. Because a stock can be so erratic from one session to the next, moving-averages or annualized data are often used in pricing model calculations to determine the fair value of an option. Once again, the larger the statistical volatility, the more expensive the option will be in the open market.

In contrast, a calculation to determine implied volatility starts with the option's price and works backward to establish a theoretical value that is equal to the market price minus any intrinsic value. It is a computed number that has more to do with the option's current price, as opposed to the price of the underlying asset. The layman's definition: implied volatility is the volatility value that makes an option's fair value equal to its present cost (or worth) in the open market.

Some traders refer to implied volatility as "premium" even though the term actually relates to the extrinsic value of an option. Since intrinsic value describes the "in-the-money" portion of an option's price, extrinsic value is simply the difference between this amount and the option's actual market price. Indeed, implied volatility and premium are related; an increase in implied volatility will raise an option's premium, as long as all the other pricing components (expiration date, underlying asset price, dividend rate, and interest rate) remain the same. There are many other factors to consider but without going into great detail, a common rule of thumb suggests that when implied volatility is low, options are effectively under-priced. Conversely, when implied volatility is high, options are effectively overpriced.

A question frequently asked by our readers is which type of volatility (statistical or implied) offers a better means of forecasting option prices. The obvious answer is that each has its strengths and limitations. Statistical volatility is based on actual (past) prices however in a dynamic environment, this data may not accurately reflect the current outlook for the underlying instrument. On the contrary, implied volatility indicates the "real-time" consensus of the market thus it more accurately represents the (price) risk inherent in a particular issue. At the same time, implied volatility can be biased by supply and demand, liquidity, and various intangibles such as recent momentum/trends or upcoming events.

Obviously, the goal of a covered-call writer is to sell options when implied volatility is high but since that condition also suggests an increased probability of an unexpected outcome, the real chore involves identifying those positions with reasonable profit potential and acceptable downside risk. We'll talk more about how we approach the selection process in a future narrative but now it's time to search for some new candidates.

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