Forecasting the Financial Market Using Random Forest -A Case Study

摘要：

In this paper, we attempt to model and forecast the movement of the excess return of a Chinese closed-ended fund. We introduce a new non-parametric random forest method to forecast the signs of excess return, and compare the results with some conventional linear models such as the random walk model (RW), ARIMA model and Support Vector Machine (SVM). The out-of-sample results show that the performance of random forest is superior to others. Moreover, we also construct the various trading strategies based on different forecasts methods. The performance of different trading strategies are contrasted and also compared with a simple buy-and-hold strategy. The results indicate that the trading strategy based on random forest methods earns significantly higher returns than other alternatives.

关键词： closed-end fund forecasting random forest trading strategy

作者: FANG Kuangnan SHIA Benchang ZHU Jianping

作者单位: School of Economics, Xiamen University, Fujian, P.R.China, 361005 School of Economics, Xiamen University, Fujian, P.R.China, 361005 Department of Statistics and Infor

会议类型: 国际会议

会议名称: The 3rd International Institute of Statistics & Management Engineering Symposium(2010 国际统计与管理工程研讨会 IISMES)

会议地点: 威海

会议语种:英文

页码: 111-120

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）