Option pricing based on the generalized lambda distribution

This article proposes the generalized lambda distribution as a tool for modeling nonlognormal security price distributions. Known best as a facile model for generating random variables with a broad range of skewness and kurtosis values, the generalized lambda distribution has potential financial applications, including Monte Carlo simulations, estimations of option-implied state price densities, and almost any situation requiring a flexible density shape. A multivariate version of the generalized lambda distribution is developed to facilitate stochastic modeling of portfolios of correlated primary and derivative securities.