Measures of Shape of a Distribution

Normal distribution, this symmetrical, bell-shaped distribution plays a central role in the mean-variance model of portfolio selection; it is also used extensively in financial risk management. The normal distribution has the following charactristics: Skewness A distribution that is not symmetrical is termed skewed. A return distribution with positive skew has frequent small losses and a…

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Forecasting Correlation of Returns: Covariance Given a Joint Probability Function

The joint probability function of two random variables X and Y, denoted P(X,Y), gives the probability of joint occurrences of values of X and Y. A formula for computing the covariance between random variables RAR_A and RBR_B is The formula tells us to sum all possible deviation cross-products weighted by the appropriate joint probability. Independence…

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Portfolio Risk Measures: Applications of the Normal Distribution

Mean-variance analysis holds exactly when investors are risk averse; when they choose investments to maximise expected utility or satisfaction; and when either (assumption 1) returns are normally distributed or (assumption 2) investors have quadratic utility functions (a concept used in economics for a mathematical representation of risk and return trade-offs). Safety-first rules focus on shortfall…

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Portfolio Expected Return and Variance of Return

The expected return on the portfolio (E(Rp))(E(R_p)) is a weighted average of the expected returns (R1 to Rn)R_1\ to\ R_n) on the component securities using their respective proportions of the portfolio in currency units as weights (w1 to w2)(w_1\ to\ w_2): Portfolio variance is as follows: Covariance Given two random variables RiR_i and RjR_j, the covariance between RiR_i and…

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