Chapter Thirteen Risky Assets
Chapter Thirteen Risky Assets
Main issue Mean-Variance Utility Budget Constraints for Risky Assets Measuring risk Capital Asset Pricing Model
Main Issue Mean-Variance Utility Budget Constraints for Risky Assets Measuring Risk Capital Asset Pricing Model
Mean of a distribution A random variable(r v )w takes values Wi,,, Ws with probabilities ■■■ s=1) The mean(expected value) of the distribution is the average value of the r.v., Elw]=uw= 2WSIS
Mean of a Distribution A random variable (r.v.) w takes values w1 ,…,wS with probabilities 1 ,...,S (1 + · · · + S = 1). The mean (expected value) of the distribution is the average value of the r.v.; E[w] w w . s s s S = = = 1
Variance of a distribution The distrilbution's variance is the rv,'s av, squared deviation from the mean var[w]=ow=2(ws-UW)"IS ariance measures the rvs variation
Variance of a Distribution The distribution’s variance is the r.v.’s av. squared deviation from the mean; Variance measures the r.v.’s variation. var[w] w (w ) . s w s s S = = − = 2 2 1
Standard deviation of a Distribution The distribution's standard deviation is the square root of its variance; st dev[w]=ow=v 2 ∑(s-12)2xs St deviation also measures the rvs variability
Standard Deviation of a Distribution The distribution’s standard deviation is the square root of its variance; St. deviation also measures the r.v.’s variability. st. dev[w] w w (w ) . s w s s S = = = − = 2 2 1