Standard deviation

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Standard deviation

The square root of the variance. A measure of dispersion of a set of data from its mean.

Historical Volatility

A measure of a security's stability over a given period of time. While there are various ways to calculate it, the most common way is to compute the average deviation from the average price over the period of time one wishes to measure. The historical volatility is often compared to the implied volatility to determine if a security is overvalued or undervalued. Generally, securities with a higher historical volatility carry more risk. It is also called realized volatility or the standard deviation. See also: Volatility.

standard deviation

A statistical measure of the variability of a distribution. An analyst may wish to calculate the standard deviation of historical returns on a stock or a portfolio as a measure of the investment's riskiness. The higher the standard deviation of an investment's returns, the greater the relative riskiness because of uncertainty in the amount of return. See also risk, variance.

Standard deviation.

Standard deviation is a statistical measurement of how far a variable quantity, such as the price of a stock, moves above or below its average value. The wider the range, which means the greater the standard deviation, the riskier an investment is considered to be.

Some analysts use standard deviation to predict how a particular investment or portfolio will perform. They calculate the range of the investment's possible future performances based on a history of past performance, and then estimate the probability of meeting each performance level within that range.

References in periodicals archive ?
The standard variances of the whole property Euclidean distances are 7.341 and 2.208, respectively, which shows that the property of building RA has great fluctuation, while pavement RA is more stable.
8(a) and 8(b) show the matching accuracy and the corresponding standard variances of GLLBP components at 30[degrees], 60[degrees], 90[degrees], 120[degrees], and 150[degrees] with the increasing value of k.
Figure 7 shows the impact of the standard variance of measurement noise on the localization accuracy.
Product SEM figures, average particle size distribution histogram, and standard variance diagram are shown in Figure 2.
Seen from the table (3) that the highest value to the central line of defense on the arithmetic to test the sense of control with a foot (2.5) and standard variance of $ (+1.14).

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