Measures of Dispersion

Dispersion is the variability around the central tendency. Absolute dispersion is the amount of variability present without comparison to any reference point or benchmark. The Range The range is the difference between the maximum and minimum values in a dataset: Range = Maximum value – Minimum value Mean Absolute Deviation (MAD) where X‾\bar{X} is the…

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…

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…

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…