Abstract
This study forecasts the option prices of Taiwan stock index options using back-propagation neural networks and Black-Scholes pricing model. The research data comprises the daily prices of sample options for the period from 2 January 2002 to 31 December 2003. The empirical evidence reveals that in a volatile market a neural network option pricing model outperforms the traditional Black-Scholes model.