標題: Using extended classifier system to forecast S&P futures based on contrary sentiment indicators
作者: Chen, AP
Chang, YH
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
公開日期: 2005
摘要: 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.
URI: http://hdl.handle.net/11536/17728
ISBN: 0-7803-9363-5
期刊: 2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS
起始頁: 2084
結束頁: 2090
Appears in Collections:Conferences Paper