Higher moments as a complementary aid for decision-making in asset allocation

In this article, the author proposes a quick method to support decision-making in selecting shares in financial markets. The method uses the statistical distributions’ higher moments of financial time series. Most people are familiar with asset allocation, even if they do not recognize that it is probably the most important investment decision that portfolio managers need to execute. Asset allocation involves the task of dividing an investment portfolio into different types or classes of assets, such as stocks, bonds, real estate, and cash. By choosing the right mix of stocks, bonds, cash, and other asset classes, an investor can ensure he is set up to reach his financial goals. It is well recognized that the distributions of asset returns are quite far from the Normal distribution. They are usually leptokurtic and asymmetrical. Extreme returns occur more frequently than would be expected for a Normal distribution. Taking advantage of the departure from normality of the distributions of asset returns, the author suggests that practitioners can compute the third and fourth moments, Skewness and Kurtosis, of each of the shares they consider could form part of their portfolios, to compare between them which ones fit their risk profile.