Option price forecasting using neural networks
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 mod...
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| Published in | Omega (Oxford) Vol. 28; no. 4; pp. 455 - 466 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Exeter
Elsevier Ltd
01.08.2000
Elsevier Pergamon Press Pergamon Press Inc |
| Series | Omega |
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| 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. |
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| AbstractList | 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. |
| Author | Tan, Chew Lim Yao, Jingtao Li, Yili |
| Author_xml | – sequence: 1 givenname: Jingtao surname: Yao fullname: Yao, Jingtao – sequence: 2 givenname: Yili surname: Li fullname: Li, Yili – sequence: 3 givenname: Chew Lim surname: Tan fullname: Tan, Chew Lim email: tancl@comp.nus.edu.sg |
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| Keywords | Neural networks Option pricing Black–Scholes model Forecasting Backpropagation Pricing Economic forecasting Risk Neural network Economic data |
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| Snippet | In this research, forecasting of the option prices of Nikkei 225 index futures is carried out using backpropagation neural networks. Different results in terms... |
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| SubjectTerms | Applied sciences Back propagation Black–Scholes model Exact sciences and technology Forecasting Inventory control, production control. Distribution Neural networks Neural networks Forecasting Option pricing Black-Scholes model Operational research and scientific management Operational research. Management science Option pricing Options markets Rates of return Securities prices Stochastic models Studies Volatility |
| Title | Option price forecasting using neural networks |
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