This is a rebroadcast of OICs webinar panel. In this deep dive discussion, Frank Fahey (representing...

# Using Volatility to Predict Future Stock Prices

10/27/2015 8:00 am EST

**Focus:** OPTIONS

*Despite its relevance to covered call writing and put-selling selections, volatility does have its limitations, which is why Alan Ellman, of TheBlueCollarInvestor.com feels it is important to fully understand the best way to take advantage of the information gleaned from volatility statistics. *

**Types of Volatility**

Historical volatility: The annualized standard deviation of actual past stock prices. Even if two stocks start and end at the same price over a period of one year, they can have very different historical volatilities as reflected in the chart below:

Note that both stocks begin and end the year priced at $100.00 per share but the *blue* stock was much more volatile over that time frame. This demonstrates that historical volatility is not based on a directional trend but rather on the amount that the price oscillates.

Our Premium Member Stock Reports give historical volatility information as it relates to the S&P 500 in our running list as shown in the screenshot below:

Implied volatility: This is the market’s forecast of the stock’s annualized standard deviation volatility based on price changes in the option. This is more important to short-term option-sellers than is historical volatility because it is forward-looking. Implied volatility will impact the time value component of an option premium only and has no effect on intrinsic value. Implied volatility is expressed as a percentage of the share price, indicating a one standard deviation move over a twelve-month time frame. Let me explain. Let’s say a stock is trading at $50.00 and has an implied volatility (again based on option pricing) of 20%. This means we can anticipate a price fluctuation 0f $10.00 (20% of $50.00) in either direction or a price range from $40.00 to $60.00. The fact that this is an annualized statistic based on one standard deviation means that the range is anticipated over a twelve month time frame and is accurate 68% of the time. This can be better visualized using a normal distribution curve:

**Note the following**:

- Share price is expected to fall between $40.00 and $60.00 68% of the time over a one year time frame
- 16% of the time, share price will be lower than $40.00
- 16% of the time, share price will be greater than $60.00

**How Is Implied Volatility Calculated?**

An option pricing model like Black Scholes is used and the following information is required:

- Stock price
- Strike price
- Expiration date
- Risk-free interest rate
- Dividends (if applicable)
- Option price

**Converting Implied Volatility Stats to Shorter-term Options**

Since we rarely sell one-year expiration options we must add one more component to our equation in predicting future price movement based on implied volatility and that is to multiply by the square root of the number of days to expiration divided by 365:

[$50.00 x 20% x SR (Days to Expiration/365)]

**Limitations of Implied Volatility When Determining Future Stock Prices**

- Does not predict direction
- Depends on market assessment (option prices) which may or may not be accurate
- Based on theoretical calculations from an option-pricing model
- Annualized stats must be converted to the time frame of the option contract
- Implied volatility stats are listed on pages 7 and 8 of our Premium Member ETF Reports.

**Discussion**

Understanding and utilizing volatility statistics are absolutely critical when trading stocks and stock options (exchange-traded funds as well). For short-term option-selling, implied volatility is more relevant than historical volatility. As helpful and useful as these data stats are, we must understand and factor in the limitations they possess so we can best utilize them in our day-to-day investment decisions.

**By Alan Ellman** of **TheBlueCollarInvestor.com**

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