Internet search data can be used for the study of market transaction behaviors. We firstly establish a concept framework to reveal the lead-lag relationship between search data and stock market based on micro-perspective of investors' behaviors. Then we develop three types of composite search indices: investor action index, market condition index, and macroeconomic index. The empirical test indicates the cointegration relationship between search indices and the annual return rate of Shanghai composite index. In the long-term trend, each percentage point increase in the three types of search indices separately, the annual return rate will increase 0.22, 0.56, 0.83 percentage points in the next month. Furthermore, Granger causality test shows that the search indices have significant predictive power for the annual return rate of Shanghai composite index.
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