Neural network design
Pricing And Hedging Short Sterling Options Using Neural Networks
International Journal of Intelligent Systems in Accounting and Finance Management
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In this paper we compare the predictive ability of the Black-Scholes Formula (BSF) and Artificial Neural Networks (ANNs) to price call options by exploiting historical volatility measures.W e use daily data for the S&P 500 European call options and the underlying asset and furthermore, we employ nonlinearly interpolated risk-free interest rate from the Federal Reserve board for the period 1998 to 2000.Using the best models in each sub-period tested, our preliminary results demonstrate that by using historical measures of volatility, ANNs outperform the BSF.In addition, the ANNs performance improves even more when a hybrid ANN model is utilized.Our results are significant and differ from previous literature.Finally , we are currently extending the research in order to: a) incorporate appropriate implied volatility per contract with the BSF and ANNs and b) investigate the applicability of the models using trading strategies.