Predicting the highest and lowest stock price before end of the day

In this paper, an ensemble model for forecasting highly complex financial time series is being introduced. To use the Autoregressive Integrated Moving Average (ARIMA) and Random Walk with Drift (RWDRIFT) models to capture the characteristics of highly complex financial time series. Experimental resu...

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書目詳細資料
主要作者: Choo, Zhi Cheng
其他作者: Quek Hiok Chai
格式: Final Year Project
語言:English
出版: 2014
主題:
在線閱讀:http://hdl.handle.net/10356/58998
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