The valuation of Taiwan stock index option price - comparison of performances between Black-Scholes and neural network model

2005 ◽  
Vol 8 (2) ◽  
pp. 355-367 ◽  
Author(s):  
Chin-Tsai Lin ◽  
Hsin-Yi Yeh
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Option Price ◽  
Stock Index ◽  
Price Comparison ◽  
Black Scholes ◽  
Index Option

A COMPARISON OF NEURAL NETWORK MODEL SELECTION STRATEGIES FOR THE PRICING OF S&P 500 STOCK INDEX OPTIONS

2007 ◽  
Vol 16 (06) ◽  
pp. 1093-1113 ◽  
Author(s):  
N. S. THOMAIDIS ◽  
V. S. TZASTOUDIS ◽  
G. D. DOUNIAS
Keyword(s):  
Neural Network ◽  
Model Selection ◽  
Network Model ◽  
Neural Network Model ◽  
Information Criteria ◽  
Stock Index ◽  
Statistical Hypothesis ◽  
Neural Network Models ◽  
Index Options ◽  
Pruning Technique

This paper compares a number of neural network model selection approaches on the basis of pricing S&P 500 stock index options. For the choice of the optimal architecture of the neural network, we experiment with a “top-down” pruning technique as well as two “bottom-up” strategies that start with simple models and gradually complicate the architecture if data indicate so. We adopt methods that base model selection on statistical hypothesis testing and information criteria and we compare their performance to a simple heuristic pruning technique. In the first set of experiments, neural network models are employed to fit the entire options surface and in the second they are used as parts of a hybrid intelligence scheme that combines a neural network model with theoretical option-pricing hints.

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