Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/14562
Title: Critical assessment of option pricing methods using Artificial Neural Networks
Authors: Andreou, Panayiotis 
Charalambous, Chris 
Martzoukos, Spiros H. 
Keywords: Economics;Neural networks;Electronic trading;Black-Scholes formula;Trading strategies;Federal Reserve;Risk assessment;Financial markets
Category: Economics and Business
Field: Social Sciences
Issue Date: 2002
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 2415 LNCS, 2002, Pages 1131-1136
Journal: Lecture Notes in Computer Science 
Conference: International Conference on Artificial Neural Networks 
Abstract: 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. We 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.
URI: https://ktisis.cut.ac.cy/handle/10488/14562
ISBN: 978-354044074-1
ISSN: 03029743
Rights: © Springer-Verlag
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers - poster -presentation

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