Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/42906
Title: Option price forecasting using neural networks
Authors: Yao, J. 
Li, Y.
Tan, C.L. 
Keywords: Black-Scholes model
Forecasting
Neural networks
Option pricing
Issue Date: 2000
Source: Yao, J.,Li, Y.,Tan, C.L. (2000). Option price forecasting using neural networks. Omega 28 (4) : 455-466. ScholarBank@NUS Repository.
Abstract: In this research, forecasting of the option prices of Nikkei 225 index futures is carried out using backpropagation neural networks. Different results in terms of accuracy are achieved by grouping the data differently. The results suggest that for volatile markets a neural network option pricing model outperforms the traditional Black-Scholes model. However, the Black-Scholes model is still good for pricing at-the-money options. In using the neural network model, data partition according to moneyness should be applied. Those who prefer less risk and less returns may use the traditional Black-Scholes model results while those who prefer high risk and high return may choose to use the neural network model results. © 2000 Elsevier Science Ltd. All rights reserved.
Source Title: Omega
URI: http://scholarbank.nus.edu.sg/handle/10635/42906
ISSN: 03050483
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

66
checked on Dec 15, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.