Investor Sentiment and the Near-Term Stock Returns: Evidence from Chinese Stock Market

2009 ◽  
Author(s):  
Yumei Jiang ◽  
Mingzhao Wang
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Investor Sentiment ◽  
Chinese Stock Market ◽  
Near Term

scholarly journals Investor sentiment by relative strength index and stock return: Empirical evidence on Vietnam's stock market

Accounting ◽  
2021 ◽  
pp. 451-456
Author(s):  
Lai Cao Mai Phuong
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Daily Basis ◽  
Relative Strength ◽  
Least Square ◽  
Trading Behavior ◽  
Strength Index ◽  
Near Term

This article examines how investor sentiment affects stock returns on Vietnam's stock market. Investor sentiment index is measured by a relative strength index (RSI) of 57 companies listed on the Ho Chi Minh Stock Exchange from January 1, 2015 to July 31, 2020. Control variables include investors' stock trading behavior, firm size, and cash flow per share. Using Fama-MacBeth regression estimation and general least square estimation (GSL) on a daily basis, both methods find the sentiment of high investors producing higher stock returns, on the contrary, the sentiment of low investors erodes stock returns. Different from the results of Brown and Cliff (2004) [Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of empirical finance, 11(1), 1-27], the article found that the investor sentiment factor plays the most important role in explaining the return of the stock market compared to the rest of the factors.

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hongli Niu ◽  
Yao Lu ◽  
Weiqing Wang
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Investor Sentiment ◽  
Wavelet Coherence ◽  
Chinese Stock Market ◽  
Frequency Method ◽  
Content Type ◽  
Time Frequency ◽  
Dynamic Relationship ◽  
Normal Period

PurposeThis paper aims to investigate the dynamic relationship between the investor sentiment and the return of various sectors in the Chinese stock market.Design/methodology/approachThe 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.FindingsThe 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 implicationsThe interindustry impact of investment sentiment on the stock market can help construct arbitrage portfolio by investors who are interested in Chinese stock market.Originality/valueThis 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.

scholarly journals Does Investor Sentiment Predict the Near‐Term Returns of the Chinese Stock Market?

2018 ◽  
Vol 20 (1) ◽  
pp. 225-233 ◽  
Author(s):  
Muhammad A. Cheema ◽  
Yimei Man ◽  
Kenneth R. Szulczyk
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Chinese Stock Market ◽  
Near Term
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