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Z-Score and Standard Deviation: What’s the Difference?

Z-Score and Standard Deviation: An Overview


Z-Score


Standard Deviation

Standard deviation is essentially a reflection of the amount of variability within a given data set. It shows the extent to which the individual data points in a data set vary from the mean. A large standard deviation means that more of your data points deviate from the norm. A small standard deviation means that more of your data points are clustered near the norm. Standard deviation can be visualized as a bell curve, with a flatter, more spread-out bell curve representing a large standard deviation and a steep, tall bell curve representing a small standard deviation.

To calculate standard deviation, first, calculate the difference between each data point and the mean. The differences are then squared, summed and averaged to produce the variance. The standard deviation is simply the square root of the variance, which brings it back to the original unit of measure.

In investing, standard deviation and Z-score can be useful tools in determining market volatility. As the standard deviation increases, it indicates that price action varies widely within the established time frame. Given this information, the Z-score of a particular price indicates how typical or atypical this movement is based on previous performance.


Bollinger Bands

Bollinger Bands are a technical indicator used by traders and analysts to assess market volatility based on standard deviation. Simply put, they are a visual representation of the Z-score. For any given price, the number of standard deviations from the mean is reflected by the number of Bollinger Bands between the price and the exponential moving average (EMA).


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About Amy Harvey

Amy R. Harvey writes forStartUps Sections In AmericaRichest.

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