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The authors investigate a new basic model for asset pricing, the hyperbolic model, which allows an almost perfect statistical fit of stock return data. After a detailed introduction into the theory they use secondary market data to compare the hyperbolic model to the classical Black-Scholes model. The authors study implicit volatilities, the smile effect, and pricing performance. Exploiting the full power of the hyperbolic model, they construct an option value process from a statistical point of view by estimating the implicit risk-neutral density function from option data. Finally, the authors present some new value-at-risk calculations leading to new perspectives to cope with model risk.
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Eberlein et al. (1998) studied this question.
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