DocumentCode :
2730849
Title :
Using extended classifier system to forecast S&P futures based on contrary sentiment indicators
Author :
Chen, An-Pin ; Chang, Yung-Hua
Author_Institution :
Institute of Information Management, National Chiao Tung University, Hsinchu, Taiwan 300, apc@iim.nctu.edu.tw
Volume :
3
fYear :
2005
fDate :
2-5 Sept. 2005
Firstpage :
2084
Abstract :
This research demonstrates the accurate forecasting performance of extended classifier system (XCS) based on contrary sentiment indicators in predicting S&P 500 futures. These indicators include volatility index, put-call ratio, and trading index. To prove that XCS based on sentiment indicators can fit the financial forecasting domain, the performance of XCS is compared with that of three trading strategies, including buy-and-hold, trend-following, and mean-reversion strategies over the same sample period. The simulation results showed that XCS based on contrary sentiment indicators possesses both forecasting accuracy and profits earning capability in the real world.
Keywords :
finance; forecasting theory; learning systems; buy and hold strategies; contrary sentiment indicators; extended classifier system; financial forecasting domain; mean reversion strategies; profits earning capability; put call ratio; trading index; trend following strategies; Artificial intelligence; Economic forecasting; Economic indicators; Environmental economics; Finance; Information management; Input variables; Lifting equipment; Neural networks; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
Type :
conf
DOI :
10.1109/CEC.2005.1554952
Filename :
1554952
Link To Document :
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