Although there are several ways to measure the volatility of a given security, analysts typically look at historical volatility. Historical volatility is a measure of past performance; it is a statistical measure of the dispersion of returns for a given security over a given period of time.
Because it allows for a more long-term assessment of risk, historical volatility is widely used by analysts and traders in the creation of investing strategies. For a given security, in general, the higher the historical volatility value, the riskier the security is. However, some traders and investors actually seek out higher volatility investments. You can calculate the historical volatility
Historical Volatility Strategies
To calculate the volatility of a given security in a Microsoft Excel spreadsheet, first determine the time frame for which the metric will be computed. For the purposes of this article, a 10-day time period will be used in the example. After determining your timeframe, the next step is to enter all the closing stock prices for that timeframe into cells B2 through B12 in sequential order, with the newest price at the bottom. (Keep in mind that if you are doing a 10-day timeframe, you will need the data for 11 days to compute the returns for a 10-day period.)
- Analysts and traders can calculate the historical volatility of a stock using the Microsoft Excel spreadsheet tool.
- Historical volatility is a measure of past performance; it is a statistical measure of the dispersion of returns for a given security over a given period of time.
- For a given security, in general, the higher the historical volatility value, the riskier the security is.
- However, some traders and investors actually seek out higher volatility investments.
In column C, calculate the interday returns by dividing each price by the closing price of the day before and subtracting one. For example, if McDonald's (MCD) closed at $147.82 on the first day and at $149.50 on the second day, the return of the second day would be (149.50/147.82) - 1, or .011, indicating that the price on day two was 1.1% higher than the price on day one.
Volatility is inherently related to standard deviation, or the degree to which prices differ from their mean. In cell C13, enter the formula "=STDEV.S(C3:C12)" to compute the standard deviation for the period.
As mentioned above, volatility and deviation are closely linked. This is evident in the types of technical indicators that investors use to chart a stock's volatility, such as Bollinger Bands, which are based on a stock's standard deviation and the simple moving average (SMA). However, historical volatility is an annualized figure, so to convert the daily standard deviation calculated above into a usable metric, it must be multiplied by an annualization factor based on the period used. The annualization factor is the square root of however many periods exist in a year.
The table below shows the volatility for McDonald's within a 10-day timeframe:
The example above used daily closing prices, and there are 252 trading days per year, on average. Therefore, in cell C14, enter the formula "=SQRT(252)*C13" to convert the standard deviation for this 10-day period to annualized historical volatility.
A Simplified Approach To Calculating Volatility
Why Volatility Is Important For Investors
While volatility in a stock can sometimes have a bad connotation, many traders and investors actually seek out higher volatility investments. They do this in the hopes of eventually making higher profits. If a stock or other security does not move, it has low volatility. However, it also has a low potential to make capital gains.
On the other hand, a stock or other security with a very high volatility level can have tremendous profit potential. But by the same token, the risk of loss is quite high.
In order to be a trader or investor that capitalizes on volatility, the timing of any trades must be perfect. Even a correct market call could end up losing money if the security's wide price swings trigger a either a stop-loss order or a margin call.