Stock prices rise and fall. The measure of the speed and extent of stock prices changes is known as volatility. The traders use volatility for a number of purposes, such as figuring out the price to pay for an option contract on a stock. You are required to figure out a stock’s standard deviation, which is a measure of how widely stock prices are spread around their average value if you **want to calculate volatility**. Calculations can be done on a spreadsheet or with a calculator.

##### Step 1

Gather stock price information. You will need at least a month of daily stock price data. However, you will get the best results by using at least six months of data. Copy and paste this information directly into a spreadsheet. You can mark Column A to represent historical **stock price trading** dates and Column B to show daily closing stock prices.

##### Step 2

Find the average price over the length of time you chose. Suppose, if you pulled out six months of information, take the average price over 183 days. This can be set up as the average function or by taking the sum of all daily prices and dividing by 183.

##### Step 3

Calculate the difference between the daily price and the average over the range of data. In case you are making use of a spreadsheet, create a Column C. This refers to this difference, by subtracting Column B from the average. Copy and paste this function down the length of the data on your spreadsheet.

##### Step 4

Square the difference. Create a Column D into which you put the square of Column C. You do this by multiplying the Column C value by itself. Now find the sum of Column D and divide by your day’s range. This is called the variance.

##### Step 5

Take the square root of the variance, using the SQRT function. When you get the result, it gives the stock’s standard deviation for the entire sample of price data. In the investor world, this number represents a measure of stock-price volatility.

##### Step 6

Check your results with a historical-volatility calculator. You need to use same data that is referred in the calculations above.