Modified TSK fuzzy system in stock price forecasting

Author

Liu, Xiangdong

Author_Institution

Langfang Polytech. Inst., Langfang, China

fYear

2010

fDate

17-19 Sept. 2010

Firstpage

621

Lastpage

624

Abstract

This paper proposes a modified version of TSK fuzzy system, called C-ascending TSK fuzzy system, to model stock price. The C-ascending TSK fuzzy system is obtained by a simple modification of the weighted membership function in TSK fuzzy system, where the recent errors are penalized more heavily than the distant errors. This procedure is based on the prior knowledge that in the non-stationary financial time series the dependency between input variables and output variables gradually changes over the time, especially, the recent past data could provide more important information than the distant past data. In the experiment, C-ascending TSK fuzzy system is tested using the Standard & Poor 500 sock index (CME-SP). It is shown that the C-ascending TSK fuzzy system with the actually ordered sample data consistently forecast is better than the standard TSK fuzzy system.

Keywords

forecasting theory; fuzzy systems; pricing; share prices; stock markets; time series; C-ascending TSK fuzzy system; Standard & Poor 500 sock index; Takagi Sugeno Kang fuzzy system; nonstationary financial time series; stock price forecasting; weighted membership function; Artificial neural networks; Forecasting; Fuzzy systems; Indexes; Stock markets; Time series analysis; Training data; Stock price forcasting; TSK fuzzy system;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-6927-7

Type

conf

DOI

10.1109/ICIFE.2010.5609436

Filename

5609436