As input data, you are given a nObs-by-nAssets matrix portRet of return series for assets in a portfolio along with an nAssets-by-1 vector portWeights of portfolio weights. Example:

 >> nObs = 504; % Number of observations

 >> nAssets = 5; % Number of assets in the portfolio

 >> portRet = randn(nObs, nAssets); % Sample portfolio return series

 >> portWeights = rand(nAssets, 1); 

 >> portWeights = portWeights/sum(portWeights); % Portfolio weights are >=0 and sum to 1.

The task is to compute the portfolio cokurtosis , which is a scalar statistic associated with the portfolio. A full description of this statistic, along with sample MATLAB code for computing it, can be found here:

http://www.quantatrisk.com/2013/01/20/coskewness-and-cokurtosis/

Write a function that accepts portRet and portWeights as input arguments and returns the scalar statistic portCokurt as its output. You can use the code at the website above as a starting point, but try to simplify and shorten it in the spirit of Cody.