Using extended classifier system to forecast S&P futures based on contrary sentiment indicators

An-Pin Chen; Yung Hua Chang

doi:10.1109/CEC.2005.1554952

Using extended classifier system to forecast S&P futures based on contrary sentiment indicators

An-Pin Chen^*, Yung Hua Chang

^*此作品的通信作者

資訊管理研究所

研究成果: Conference contribution › 同行評審

11 引文斯高帕斯（Scopus）

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.

原文	English
主出版物標題	2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings
頁面	2084-2090
頁數	7
DOIs	https://doi.org/10.1109/CEC.2005.1554952
出版狀態	Published - 2005
事件	2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 - Edinburgh, Scotland, 英國持續時間: 2 9月 2005 → 5 9月 2005

出版系列

名字	2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings
卷	3

Conference

Conference	2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005
國家/地區	英國
城市	Edinburgh, Scotland
期間	2/09/05 → 5/09/05

存取文件

10.1109/CEC.2005.1554952

其它文件與鏈接

Link to publication in Scopus

引用此

@inproceedings{7c3220748b394023998ccde67b6c7be4,

title = "Using extended classifier system to forecast S&P futures based on contrary sentiment indicators",

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.",

author = "An-Pin Chen and Chang, {Yung Hua}",

year = "2005",

doi = "10.1109/CEC.2005.1554952",

language = "English",

isbn = "0780393635",

series = "2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings",

pages = "2084--2090",

booktitle = "2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings",

note = "2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 ; Conference date: 02-09-2005 Through 05-09-2005",

}

Chen, A-P & Chang, YH 2005, Using extended classifier system to forecast S&P futures based on contrary sentiment indicators. 於 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings. 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings, 卷 3, 頁 2084-2090, 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005, Edinburgh, Scotland, 英國, 2/09/05. https://doi.org/10.1109/CEC.2005.1554952

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AU - Chen, An-Pin

AU - Chang, Yung Hua

PY - 2005

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N2 - 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.

AB - 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.

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SN - 0780393635

T3 - 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings

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BT - 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings

T2 - 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005

Y2 - 2 September 2005 through 5 September 2005

ER -

Using extended classifier system to forecast S&P futures based on contrary sentiment indicators

摘要

出版系列

Conference

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