Prediction of the Price of Stock Index Futures Based on SVM and Triangular Fuzzy Information Granulation Concerning Investors Sentiment

Yan LIN, Jianhui YANG

Abstract


This paper proposed a hybrid model based on triangular fuzzy information granulation and SVM to predict the trend and fluctuation range of the price of stock index futures. Firstly, the original data is processed by triangular fuzzy information granulation. Then, the cross validation method is used to obtain the parameters of SVM. Also some significant factors concerning investors sentiment are considered to improve the forecast accuracy of the hybrid model. At last, the hybrid model is used to perform empirically study based on HS300 stock index futures data after fuzzy information granulation. The empirical analysis showed that the hybrid model owns the better preformation for the prediction of the change trend and range of the price of stock index futures. After concerning investors sentiment, the accuracy of prediction is also improved effectively.


Keywords


Stock index future; Fuzzy information granulation; Support Vector Machine (SVM); Investors sentiment

Full Text:

PDF

References


Bargiela, A., & Pedrycz, W. (2003). Granular computing: An introduction. Dordrecht: Kluwer Academic Publishers

Chiu, L., (1994). Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy System, 2(3).

Dubois, D., & Prade, H. (1990). Rough fuzzy sets and fuzzy rough sets. International Journal of General Systems, 17(2), 191-209.

Gencay, R., & Qi, M. (2001). Pricing and hedging derivatives securities with neural networks: Bayesian regularization, early stopping and bagging. IEEE Transactions on Neural Networks, 12(4), 726-734.

Huang, C. J. (2011). Using genetic algorithm optimization SVM to construction of investment model. International Journal of Digital Content Technology, 5(1), 123-132.

Zadeh, A. (1997). Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems, 19(1), 111-127.

Zhang, L., & Zhang, B. O. (2003). Theory of fuzzy quotient space (methods of fuzzy granular computing). Journal of Software, 14(4).

Zhang, H. Y., & Lin, H. (2009). Option price forecasting model by applying hybrid neural network and genetic algorithm. Journal of Industrial Engineering Management, 123(1), 59-87.




DOI: http://dx.doi.org/10.3968/n

Refbacks

  • There are currently no refbacks.


Copyright (c) 2016 Yan LI, Jianhui YANG

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Share us to:   

Reminder

  • How to do online submission to another Journal?
  • If you have already registered in Journal A, then how can you submit another article to Journal B? It takes two steps to make it happen:

1. Register yourself in Journal B as an Author

  • Find the journal you want to submit to in CATEGORIES, click on “VIEW JOURNAL”, “Online Submissions”, “GO TO LOGIN” and “Edit My Profile”. Check “Author” on the “Edit Profile” page, then “Save”.

2. Submission

  • Go to “User Home”, and click on “Author” under the name of Journal B. You may start a New Submission by clicking on “CLICK HERE”.


We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
[email protected]; [email protected]; [email protected]

 Articles published in Management Science and Engineering are licensed under Creative Commons Attribution 4.0 (CC-BY).

 MANAGEMENT SCIENCE AND ENGINEERING Editorial Office

Address:1055 Rue Lucien-L'Allier, Unit #772, Montreal, QC H3G 3C4, Canada.

Telephone: 1-514-558 6138
Http://www.cscanada.net Http://www.cscanada.org

Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures