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Standard deviation is a measure of total risk, or both systematic and unsystematic risk. Unsystematic risk can be diversified away, systematic risk cannot and is measured as Beta.

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Q: Does standard deviation measure systematic or unsystematic risk?
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Annualized standard deviation?

http://www.hedgefund.net/pertraconline/statbody.cfmStandard Deviation -Standard Deviation measures the dispersal or uncertainty in a random variable (in this case, investment returns). It measures the degree of variation of returns around the mean (average) return. The higher the volatility of the investment returns, the higher the standard deviation will be. For this reason, standard deviation is often used as a measure of investment risk. Where R I = Return for period I Where M R = Mean of return set R Where N = Number of Periods N M R = ( S R I ) ¸ N I=1 N Standard Deviation = ( S ( R I - M R ) 2 ¸ (N - 1) ) ½ I = 1Annualized Standard DeviationAnnualized Standard Deviation = Monthly Standard Deviation ´ ( 12 ) ½ Annualized Standard Deviation *= Quarterly Standard Deviation ´ ( 4 ) ½ * Quarterly Data


What is the difference between standard error and standard deviation?

Standard error is the difference between a researcher's actual findings and their expected findings. Standard error measures the accuracy of one's predictions. Standard deviation is the difference between the results of one's experiment as compared with other results within that experiment. Standard deviation is used to measure the consistency of one's experiment.


Can a standard deviation be less than 1?

Yes. Standard deviation depends entirely upon the distribution; it is a measure of how spread out it is (ie how far from the mean "on average" the data is): the larger it is the more spread out it is, the smaller the less spread out. If every data point was the mean, the standard deviation would be zero!


What determines the standard deviation to be high?

Standard deviation is a measure of the scatter or dispersion of the data. Two sets of data can have the same mean, but different standard deviations. The dataset with the higher standard deviation will generally have values that are more scattered. We generally look at the standard deviation in relation to the mean. If the standard deviation is much smaller than the mean, we may consider that the data has low dipersion. If the standard deviation is much higher than the mean, it may indicate the dataset has high dispersion A second cause is an outlier, a value that is very different from the data. Sometimes it is a mistake. I will give you an example. Suppose I am measuring people's height, and I record all data in meters, except on height which I record in millimeters- 1000 times higher. This may cause an erroneous mean and standard deviation to be calculated.


Why standard deviation is more often used than variance?

Both variance and standard deviation are measures of dispersion or variability in a set of data. They both measure how far the observations are scattered away from the mean (or average). While computing the variance, you compute the deviation of each observation from the mean, square it and sum all of the squared deviations. This somewhat exaggerates the true picure because the numbers become large when you square them. So, we take the square root of the variance (to compensate for the excess) and this is known as the standard deviation. This is why the standard deviation is more often used than variance but the standard deviation is just the square root of the variance.

Related questions

Do units of measure follow the standard deviation?

Units of measure do follow the standard deviation.


What is standard deviation used for?

Standard deviation is a measure of the spread of data.


Why do we need the standard deviation?

The standard deviation is a measure of the spread of data.


Does standard deviation and mean deviation measure dispersion the same?

No. The average of the deviations, or mean deviation, will always be zero. The standard deviation is the average squared deviation which is usually non-zero.


Why standard deviation is best measure of dispersion?

standard deviation is best measure of dispersion because all the data distributions are nearer to the normal distribution.


Why standard deviation is better measure of variance?

1. Standard deviation is not a measure of variance: it is the square root of the variance.2. The answer depends on better than WHAT!


What is the minimum data required for standard deviation?

The standard deviation is a measure of how spread out the numbers are. Three points is needed to calculate a statistically valid meaningful standard deviation.


What does one standard deviation mean?

Standard deviation is a measure of variation from the mean of a data set. 1 standard deviation from the mean (which is usually + and - from mean) contains 68% of the data.


How do you measure the risk of a single asset?

The total risk of a single asset is measured by the standard deviation of return on asset. Standard deviation is the square root of variance. To measure variance, you must have some distribution/ possibility of asset returns. However, the relevant risk of a single asset is the systematic risk, not the total risk. Systematic risk is the risk that cannot be diversified away in a portfolio. Systematic risk of an asset is measured by the Beta. Beta can be found using Regression (between market return and asset's return) or Covariance formula.


What does standard deviation tell about distribution and varity?

It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.


How do you use standard deviation?

Standard deviation is a measure of how spread out a set of numbers are from each other. It has a variety of uses in statistics.


How do you calculation standard deviation of concrete cubes?

You cannot calculate standard deviation for objects such as concrete cubes - you can only calculate standard deviation for some measure - such as side length, surface area, volume, mass, alkalinity or some other measure.