Capturing the volatility smile of options on high-tech stocks—A combined GARCH-neural network approach

Gunter Meissner and Noriko Kawano

Journal of Economics and Finance, 2001, vol. 25, issue 3, 276-292

Abstract: A slight modification of the standard GARCH equation results in a good modeling of historical volatility. Using this generated GARCH volatility together with the inputs: spot price divided by strike, time to maturity, and interest rate, a generated Neural Network results in significantly better pricing performance than the Black Scholes model. A single Neural Network for each individual high-tech stock is able to adapt to the market inherent volatility distortion. A single Network for all tested high-tech stocks also results in significantly better pricing performance than the Black-Scholes model. Copyright Academy of Economics and Finance 2001

Date: 2001
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DOI: 10.1007/BF02745889

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