The paper “The Progress of Research on Empirical Asset Pricing Based on Network Big Data Mining”, co-authored by Professor Xueyong ZHANG of the School of Finance and his doctoral student Yuling WU, was recently published in the 6th issue of “Economic Perspectives” in 2018.

Abstract: With the rapid development of computer science and the widespread use of the Internet, the Internet records people's increasing network behavior. The big data of the network provides the possibility to analyze investors' concerns and sentiments. Empirical asset pricing based on network big data mining has gradually attracted the attention of scholars at home and abroad. This paper summarizes the main research methods of investor's concern and sentiment using big data in recent years. This paper collates researches on four types of network big data, including internet news data, search engine data, social network data, and web forum data. In addition, this paper analyses the impact of investors' concerns and sentiments on asset prices and the transmission mechanism.

Keywords: Network Big Data; Asset Pricing; Investor Concern; Investor Sentiment