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Options: Standard Deviation Is A Sound Tool For Trade Timing

Should options traders rely on implied volatility?


This relies on estimates and assumes that current prices of underlying and option are accurate. Too many traders end up believing that volatility leads price when, in fact, it is the other way around. Volatility is a reflection of price behavior.

With this in mind, historical volatility is exact and visible, and can be used to determine when to enter and exit trades. It is far more reliable and accurate than the option's implied volatility.

A stock's historical volatility measures its tendency to move up or down in price. Faster and larger movements in price represent high volatility and unpredictability for a stock's price in the near term. Historical volatility, in fact, is the most reliable indicator of market risk.

Under the formula used to measure volatility, the standard deviation in price change serves as the basis for identifying the percentage of volatility. But the problem with any unadjusted statistical average is that it does not account for price spikes, which distort the picture.

For example, a stock's price range over the past 52 weeks has been between $50 and $55 per share. About six months into the year, a rumor was floated that the company was the target of a merger and that the price that was to be offered was $62 per share. The price spiked up in one day, and then returned to its previous range when the rumor turned out to be unfounded.

This price spike will distort the calculation because it creates a wide divergence in price even though it was not valid. A more accurate method would be to eliminate the price spike and then calculate volatility. With this in mind, any calculation should exclude price spikes because they are not representative of the prevailing statistical trend.

The method of calculation can be inaccurate if the price is distorted during the period under study. Many investors also misunderstand volatility, thinking it is the same as a stock's beta. Volatility measures the degree of price movement, while beta measures a stock's price reaction to changes in the broader market.

You can calculate historical volatility by applying an Excel formula for as many days as you want to study. Because volatility is a very current attribute of stock prices, you do not need to include a large number of recent sessions. Following is the set of inputs for calculation of historical volatility on an Excel worksheet, assuming you are performing the calculation for the last 15 sessions.

Column A - enter each day's closing price beginning in row 1 and continuing to row 15.

Column B - calculate the daily net change (divide each day by the prior day, and subtract 1.

Column C - multiply Column B by 100. Formula is =SUM(C1*100) Copy this and then paste to other rows in Column C.

Column D, row 15 - calculate the standard deviation of Column C. The formula for the last row of Column D is: =STDEV(C1:C15)

Column E, row 15 - annualize the standard deviation based on average trading days per year of 252. This is the square root of standard deviations. The formula for the last row of Column E is: =SQRT(252)*D15

Measuring volatility is crucial for several reasons. First and foremost, it quantifies risk. Second, high volatility can affect both profitability and cash flow, based on investor perceptions about a company's overall stability. Third, speculation based on volatility may itself affect the price of stock in the short term, further distorting volatility over the longer period.

Volatility one of many key ingredients in stock selection. However, it should be measured accurately in order to be useful. This means removing price spikes and studying performing a calculation of historical volatility. Once you have entered values into the Excel worksheet, you can continue adding new closing prices each day.

In addition, remember that volatility and beta are entirely different measurement. Finally, a distinction should be made -- but often is overlooked -- between price volatility and price direction.

Price direction may have growing or shrinking momentum, and that is an important consideration in selecting and timing the purchase of a company's stock. Volatility measures the degree of change, but does not predict price direction. In fact, fast up-and-down price movement may result in high volatility but no directional change of significance.

Considering the flaws of statistical measurement, an alternative method of calculating volatility makes sense. You can set up a visual representation of volatility by overlaying Bollinger Bands on your price chart. The band width (from upper to lower bands) is a visual summary of current volatility, and you can see expanding and contracting levels over time.

Bollinger Bands represents a "probability matrix" for timing of options trades, all based on historical volatility. Many signals are generated and are worth investigating further. These include the Bollinger squeeze, M top, W bottom, and island cluster. When prices move above the upper band or below the lower band, expect a retracement. It is rare for trading outside of the bands to last more than a few days during a strong bullish or bearish trend.

Using a system combining calculated historical volatility with Bollinger Bands enables the visualization of probabilities, so that timing of trades is vastly improved, both entry and exit.

The underlying historical volatility is most visible in the breadth of trading, and options traders realize that the reliability or consistency of breadth defines levels of option premium. So for many more conservative traders, the first step is picking the stock; and only then do you consider what types of options traders to enter.

Michael Thomsett blogs at, Seeking Alpha, and several other sites. He has been trading options for 35 years and has published books with Palgrave Macmillan, Wiley, FT Press and Amacom, among others. He is the author of Investing in Energy. You can find this book at and Barnes and Noble