A simple and readily computable algorithm is developed for approximating the low moments of order deviates from any continuous distribution. The results are compared with those obtained from exact closed form moments, obtained from quadrature as well as other non-Monte Carlo integral computations

Lognormal random variables appear naturally in many engineering disciplines, including wireless communications, reliability theory, and finance. So, too, does the sum of (correlated) lognormal random variables. Unfortunately, no closed form probability distribution exists for such a sum, and it...

This paper studies the behavior of the conventional measures of skewness and kurtosis when the data generator process is a distribution which does not possess variance or third or fourth moment and assesses the robustness of the alternative measures for these particular cases. I first show that...

At its core, portfolio and risk management is about gathering and processing market-related data in order to make effective investment decisions. To this end, risk and return statistics are estimated from relevant financial data and used as inputs within the investment process. It is this...

When decomposing differences in average economic outcome between two groups of individuals, it is common practice to base the analysis on logarithms if the dependent variable is nonnegative. This paper argues that this approach raises a number of undesired statistical and conceptual issues...