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L1 07 Statistical Concepts and Market Returns > G > Flashcards

Flashcards in G Deck (8)
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The difference between the maximum values and minimum values in a data set

Calc: Range = Max Value - Min Value


Mean Absolute Deviation

Calc: Return - Arithmetic Return + ... / N


Most common measures of dispersion (absolute dispersion: "the amount of variability present without comparison to any reference point or benchmark.")

Range: Max Value - Min Value INtep: A larger range of return implies more risk

MAD - "The mean absolute deviation uses all of the observations in the sample and is thus superior to the range as a measure of dispersion" Addresses the issue that the SD of the mean always equals 0 (because the -N's cancel each other out). Disadv. Difficult to manipulate mathematically (variance is better for this). Interp: A hhigher MAD implies more risk

Variance (population)

Standard Deviation (population)


Population Variance (must know ev. member of a population aka need knowledge of pop. mean Mu)((parameter of a distribution, risk measure)

"Variance is defined as the average of the squared deviations around the mean.

"the population variance is the arithmetic average of the squared deviations around the mean."
adv: "variance takes care of the problem of negative deviations from the mean canceling out positive deviations by the operation of squar- ing those deviations"

Measured in squared units - also, it's the SD^2


Standard Deviation (parameter of a distribution, risk measure)

Standard deviation is the positive square root of the variance."

SD is useful to return variance to original units (since variance is measured in ^2'ed units): Expressed in the same unit of measurement as the observations


Sample Variance

The statistic that measures the dispersion in a sample


Sample Standard Deviation



"The mean absolute deviation will always be less than or equal to the standard deviation because the standard deviation gives more weight to large deviations than to small ones...

(remember, the deviations are squared)."

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