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Volatility is defined as the price range for a period, divided by the average price for the period: For instance, on 3/18/2010 the average price was 128.1 with a range of 1.30, indicating a Daily Volatility of 1%. The Daily Volatility is obtained by dividing the daily range by the daily average. A longer Volatility period such as Weekly Volatility is obtained by dividing the weekly price range by the weekly mean price. This is a different concept from the weekly average of daily volatility. For reference, the price is plotted in red. The remaining marks on the plot correspond to the Volatility measured across several time intervals. Investors often make a distinction between the concept of Volatility, and the concept of Risk. Academics define them to be exactly equivalent, but as can be seen here, there is good reason to distinguish between the levels of volatility or risk experienced across different time frames. During 30 years, the Average Quarterly Volatility of IBM stock price has been 20% while the Average Daily Volatility has been 2%. |
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You may be familiar with the "yield curve" which shows how interest bearing yields vary according to term. These Volatility Curves each apply to a discrete time interval. From left to right, each position plots the Volatility associated with increasing intervals of time. The relationship between the length of time, and the expected change in price, is not linear, as is demonstrated by this chart. |
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This histogram is a frequency distribution of Daily Volatility, corresponding to the green points on the first chart on this page. |
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Similarly, the purple points on the top chart, the Quarterly Volatility Values, are subjected to frequency distribution here. |
Refined Volatility Risk Analysis for IBM : |
| In the news, Friday, March 19, 2010: An unfavorable condition has developed with Cincinnati Financial Corporation, ticker symbol CINF. Also, there are breaking events concerning Pre-Paid Legal (PPD) and Electronic Data Systems (EDS) |