Abstract
This article provides a mathematical and empirical investigation of the reasons for the presence of skewness and kurtosis in financial data. The results indicate that this phenomenon is triggered by higher-order moment dependencies in the data, such as asymmetric and conditional volatility. Moreover, the article develops and tests successfully a skewed extension of the generalized error distribution (SGED), which is then used to model European call option prices. Under the standard assumptions of risk neutrality, normality of log-returns, and absence of arbitrage opportunities, the SGED model yields as special cases several well-known models for pricing options on stocks, stock indices, currencies, and currency futures.
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