Topic: The Measurement of News Media Sentiment and its Impact on Peer-to-Peer (P2P) Lending

Lecturer: Jingyi WANG is a doctorial student at National School of Development, Peking University. The main research areas are Financial Technology, Emotions and Markets, and Machine Learning. Jingyi WANG’s research results were published in famous journals such as China Economic Quarterly, Journal of Financial Research, and China Economic Journal.

Time: Dec. 12, 2018, Wednesday, 12:30-13:30

Venue: Room 913, Main Building in city campus of CUFE

Moderator: Kunyu TAO, Assistant Professor in the School of Finance at CUFE

Abstract: How does news sentiment affect behaviour in a fast-growing innovative segment of the Chinese financial market? This paper addresses this question by making two major efforts. First, employing natural language processing and deep learning techniques, we construct the “China FinTech Sentiment Indices (CFSIs)”, making use of over 17 million Chinese language news articles published between January 2013 and August 2017. The CFSIs cover the dimensions’ attention, positive sentiment and negative sentiment. And, second, we examine impacts of such news sentiment on China’s fast growing and practically unregulated Peer-to-Peer (P2P) lending market. We find that positive sentiment tends to raise trading volume and negative sentiment tends to reduce it asymmetrically. Additionally, we also discover that P2P trading volumes respond positively to the interest rates granted to lenders and negatively to the market liquidity conditions. Hence, basic market mechanisms appear to function normally in this nascent financial market segment.