Select TRUE if the statement is correct and FALSE if the statement is wrong.

True	False
		Variance and standard deviation provide one measure of uncertainty or the risk in outcomes.
		Fat tails implies there is higher probability mass in extreme events in the tails.
		We use the probability weighted average of the outcomes as a measure of central tendency.
		Fat tails implies that there is lower probability mass in extreme events in the tails.
		When a distribution is skewed to the left, the standard deviation will underestimate risk.
		Standard deviation measures diversifiable risk.
		Normal distribution has a skewness equal to 3.
		When a distribution is skewed to the left, the standard deviation will overestimate risk.
		Risk refers to the chance that some unfavorable event will occur, and a probability distribution is completely described by a listing of the likelihood of unfavorable events.
		The higher the variability or the volatility of the outcomes is, the higher will be the standard deviation.
		"Investors panic causing security prices around the globe to fall precipitously" is an example of systematic risk.
		Expected returns are based on the probabilities of possible returns.
		The risk that results from the use of debt capital is unsystematic risk.
		Standard deviation measures total risk, which includes systematic and unsystematic risk.
		If you want to have an indication of the expected rate of return for an investment, you would prefer to look at the arithmetic average return over the period of interest.
		We use the standard deviation as the measure of the dispersion for a distribution.
		Normal distribution has a kurtosis equal to 0.
		It is obvious that securities (stocks) have similar degrees of systematic risk.
		Arithmetic mean of returns is a common measure for risk of return.
		Unsystematic risk is measured by standard deviation.
		When a distribution is skewed to the right, the extreme negative values dominate and the measure is negative.