Noise trading and stock returns: evidence from China

Abstract

Purpose -The purpose of this paper is to analyze the trading behaviors of retail investors and investigate their impacts on stock returns. Design/methodology/approach -As retail investors are considered as the main noise traders in the capital market, using the trading records of Chinese retail investors from 2005 to 2009, the authors study their trading preferences and the correlation of their trades. Then, they use a multifactor model to test whether the co-movement of stock returns could be explained by individual sentiment. Findings -The authors' results show that the small-cap stocks are obviously preferred by retail investors. Meanwhile, the net stock demands of retail investors are systematically correlated, even when the effect of market risk is excluded. In the perspective of the net stock demands, the authors use BSI to measure the individual sentiment, finding that individual sentiment plays an important role in the formation of the cross-section of stock returns. However, the authors' results imply that BSI is a reverse indicator to predict the future returns, which implies that the trading behaviors of retail investors are irrational. Originality/value -Consistent with behavioral theory, the authors' findings support the viewpoint that stock returns could be affected by the systematic correlated trading of retail investors. To some extent, their findings highlight the need to know more details of individual investors' trading behaviors through which the fluctuations of asset prices can be better understood.

Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature

“…Osler (1998) identifies noise traders in the U.S. market using the "head-and-shoulder" chart pattern-again, this model is limited to trading based on technical analysis. Lee et al (2002), Verma and Verma (2006) and Hu and Wang (2013) fail to control for the effects of firm-specific factors. The rest of this section focuses on Ramiah and Davidson (2007) and Davidson and Ramiah (2010) as a continuation of the work of De Long et al (1990) and Shefrin and Statman (1994).…”

“…Several studies have been conducted to quantify noise, including Sias et al (2001), De Long et al (1990), Osler (1998), Lee et al (2002), Verma andVerma (2006), Ramiah andDavidson (2007) and Hu and Wang (2013). Others incorporate noise trading in their models, including Blume and Easley (1994), Barberis, Shleifer and Vishny (1998), Daniel, Hirshleifer and Subrahmanyam (1998) and Shefrin and Statman (1994).…”

Can Stock Investor Sentiment Be Contagious in China?

“…Further, Chinese investor sentiment is more sensitive to different financial information, such as the wax and wane of other financial markets. Cao et al [24] indicate that stock, bond, and foreign exchange markets show a strong correlation in China because investors deal with frequent noise trading based on their intuition rather than reasonable estimation [25]. Regulators will confront more difficulties in sustaining market efficiency and stability.…”

An application of the information-adjusted noise model to the Shenzhen stock market

“…Attemps have been made to quantify noise, including Sias et al (2001), De Long et al (1990, Osler (1998), Lee et al (2002), Verma and Verma (2006), Ramiah and Davidson (2007) and Hu and Wang (2013). Modes that incorporate noise have been developed by Blume and Easley (1994), Barberis et al (1998), Daniel et al (1998) and by Shefrin and Statman (1994).…”

“…Osler (1998) identifies noise traders in the US market using the head-and-shoulder chart pattern but his model is limited to trading based on technical analysis. Furthermore, Lee et al (2002), Verma and Verma (2006) and Hu and Wang (2013) fail to control for the effects of firm-specific factors.…”