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This study firstly proposes Meta-Investment Strategy, derived from the concept of Meta-Search in network and Meta-Cognition in psychology. We compare enormous web information to all A shares in China, process of searching information to stock selection and search engines to equity funds. Based on the sector rotation theory and decision tree model, through the construction of indicator system and the statistical model, some stock selection rules according to funds information can be extracted. After classifying the period from 2016.02 to 2016.04 as recovery, we selected finance industry. By importing 12 stock indicators of all the component stocks in finance industry as input variables and whether it is heavily held by stocks funds as target variable, a decision tree model is constructed. Finally, by entering data of the last quarter in 2015, the predictive classification results are obtained. Result shows that Meta-Investment Strategy outperformed CSI300 and CSI300 of Finance Sector (000914) and obtained significant excess return from 2016.02.01 to 2016.04.30.
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