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dc.contributor.authorColeman, Thomas Fen_US
dc.contributor.authorLi, Yuyingen_US
dc.contributor.authorVerma, Arunen_US
dc.description.abstractUsing market European option prices, a method for computing a {\em smooth} local volatility function in a 1-factor continuous diffusion model is proposed. Smoothness is introduced to facilitate accurate approximation of the true local volatility function from a finite set of observation data. It is emphasized that accurately approximating the true local volatility function is crucial in hedging even simple European options, and pricing exotic options. A spline functional approach is used: the local volatility function is represented by a spline whose values at chosen knots are determined by solving a constrained nonlinear optimization problem. The optimization formulation is amenable to various option evaluation methods; a partial differential equation implementation is discussed. Using a synthetic European call option example, we illustrate the capability of the proposed method in reconstructing the unknown local volatility function. Accuracy of pricing and hedging is also illustrated. Moreover, it is demonstrated that, using a different constant implied volatility for an option with different strike/maturity can produce erroneous hedge factors. In addition, real market European call option data on the S and P 500 stock index is used to compute the local volatility function; stability of the approach is demonstrated.en_US
dc.format.extent646476 bytes
dc.format.extent2423319 bytes
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleReconstructing the unknown volatility functionen_US
dc.typetechnical reporten_US

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