Baidu index and predictability of Chinese stock returns

Dehua Shen, Yongjie Zhang (), Xiong Xiong and Wei Zhang
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Yongjie Zhang: Tianjin University
Xiong Xiong: Tianjin University
Wei Zhang: Tianjin University

Financial Innovation, 2017, vol. 3, issue 1, 1-8

Abstract: Abstract A number of studies have investigated the predictability of Chinese stock returns with economic variables. Given the newly emerged dataset from the Internet, this paper investigates whether the Baidu Index can be employed to predict Chinese stock returns. The empirical results show that 1) the Search Frequency of Baidu Index (SFBI) can predict next day’s price changes; 2) the stock prices go up when individual investors pay less attention to the stocks and go down when individual investors pay more attention to the stocks; 3) the trading strategy constructed by shorting on the most SFBI and longing on the least SFBI outperforms the corresponding market index returns without consideration of the transaction costs. These results complement the existing literature on the predictability of Chinese stock returns and have potential implications for asset pricing and risk management.

Keywords: Stock return predictability; Baidu index; Trading strategy; Financial Big data analytics; Chinese stock market; Investor inattention (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (22)

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DOI: 10.1186/s40854-017-0053-1

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