Pricing Options with Futures-style Margining: A Genetic Adaptive Neural Network ApproachTaylor & Francis, 2000 - 206 pages This book examines the applicability of a relatively new and powerful tool, genetic adaptive neural networks, to the field of option valuation. A genetic adaptive neural network model is developed to price option contracts with futures-style margining. This model is capable of estimating complex, non-linear relationships without having prior knowledge of the specific nature of the relationships. Traditional option pricing models require that the researcher or practitioner specify the distribution of the underlying asset. In addition, the methodology is able to easily accommodate additional inputs(something that cannot be preformed with existing models. Since 1973, options on stock have been traded on organized exchanges in the United States. An option on a stock gives the option owner the right to buy or sell the stock for a pre-set price.. Since the introduction of stock options, the options market has experienced tremendous growth and has spawned even more exotic types of derivative securities. Obviously, valuing these securities is an issue of great importance to investors and hedgers in the financial marketplace. Existing pricing models produce systematic pricing errors and new models have to be developed for options with differing characteristics. The genetic adaptive neural network is found to provide more accurate valuation than a traditional option pricing model when applied to the 3-month Eurodollar futures-option contract traded on the London International Financial Futures and Options Exchange. |
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Contents
Literature Review | 9 |
02294 | 58 |
Methodology and Data | 65 |
Results | 115 |
Conclusions and Suggestions for Future | 187 |
193 | |
201 | |
Other editions - View all
Pricing Options with Futures-Style Margining: A Genetic Adaptive Neural ... Alan White Limited preview - 2014 |
Pricing Options with Futures-Style Margining: A Genetic Adaptive Neural ... Alan White Limited preview - 2014 |
PRICING OPTIONS WITH FUTURES-STYLE MARGINING: A Genetic Adaptive Neural ... ALAN. WHITE No preview available - 2016 |
Common terms and phrases
01 level 3-month Eurodollar futures Adaptive Neural Network American call option American options B-S model Black-Scholes BOPM buyer call and put call option price call price CGANN Chen & Scott commodity continuous dividend deep in-the-money deep out-of-the-money degree of moneyness derivative securities Descriptive Statistics early exercise equation Error MAE Eurodollar futures contract European exercise price expiration Figure Frequency Distribution function futures contract futures price futures-style margining futures-style options GANN approximation GANN's GANNs ability Genetic Adaptive Neural hidden layer nodes Holdout Data Set holdout sample implied volatilities inputs interest rate futures maturity MSE and MAE option pricing model options on futures options with futures-style out-of-the-money out-of-the-money puts p-value PGANN portfolio pricing biases put option prices put price rejected risk-free rate simulated call Simulation Data Set Simulation Training Data stock price strike price strike rate Training Data Set training sample variables volatility Wiener process Wilcoxon Signed-Ranks Test дс
Popular passages
Page 197 - Bond rating: a non-conservative application of neural networks.", Proceedings of the IEEE International Conference on Neural Networks, San Diego, pp.443-450, 1988.