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Standard deviation is often used as a measure to estimate future moves of an asset such as a stock (volatility). Although, price changes do not have a normal distribution, some technical analysts assume that it is the case and use this assumption to predict future price move. If the price changes were normally distributed, a standard deviation of two would mean that 95% of values should lie within two standard deviations of the mean.
The current item is a pivot table that shows the average stock standard deviation for each industry. Each row of the table corresponds to an industry. In columns, you can see three average stock standard deviations that correspond to three different periods (10, 50 and 250 bars).
The calculation is based on the last historical data (Last quote date) and it consists of calculating the standard deviation or volatility of each stock, grouping these stocks by industry and then averaging the values that are from the same industry.
Example:
In the above table, the "Agriculture Biotech" industry has an average 50-bar standard deviation of 0.483, while the "Applications software" industry has a standard deviation of 0.966.
A cell is colored in blue when the standard deviation is lower than 0.5 and it is colored in red when its value is higher than 4. This will let you quickly identify the industries that have the highest or lowest volatility.
