Does investor sentiment differently affect stocks in different sectors? Evidence from China

Purpose - This paper aims to investigate the dynamic relationship between the investor sentiment and the return of various sectors in the Chinese stock market. Design/methodology/approach - The wavelet coherence and wavelet phase angle approaches are used to study the lead–lag associations between sentiment index and stock returns in a time–frequency way. The multiscale linear and nonlinear Granger causality tests are performed to explore whether there is a causality between them. Findings - The empirical results show that during normal period, investor sentiment index has a stronger relationship with stock returns of industrials, consumer discretionary, health care, utilities, real estate and financial sectors. In crisis period, investor sentiment has a significant positive relationship with all industry sectors. In the short term, there is bidirectional causality between investor sentiment and stock returns of all sectors. In the medium and long run, almost all sector stock returns Granger-cause the investors' sentiment index but investor sentiment does not Granger-cause all sectors, which is in contrast to the developed markets. Practical implications - The interindustry impact of investment sentiment on the stock market can help construct arbitrage portfolio by investors who are interested in Chinese stock market. Originality/value - This paper focuses on the industry sector differences of investor sentiment impact on the Chinese stock market. As far as the authors know, this is the first paper to explore the time–frequency relationship between sentiment index and industry stock returns in China using the time–frequency method based on wavelet coherence, which considers the heterogeneity of different types of investors' responses to various economic and financial events.