 |
Financial economics includes the study of the density of 'excess returns,' having skewness, fat tails, and excess kurtosis. We illustrate it using monthly data on a mutual fund. The nonnormality of impacts measurement of potential losses by 'value at risk' (VaR). Since finance literature has mostly ignored Azzalini's [1] skew normal (SN) density, our aim is to illustrate its implementation using Mathematica and mathStatica [2]. We use a location-scale version of the SN distribution, create its likelihood function, and use maximum likelihood (ML) to estimate its parameters. We illustrate it with data for a mutual fund and report the ML estimates, quantiles of , and the VaR.
|
|
For the newest resources, visit Wolfram Repositories and Archives »
