Noise Trader Risk-Evidence from China’s Stock Market
DOI:
https://doi.org/10.66674/mw7nmf60Keywords:
Noise trading, variance ratio, volatility asymmetry, EGARCH-M, market efficiency, behavioural financeAbstract
Research Question: This paper examines the prevalence of noise trading and volatility asymmetry in the Chinese stock market. Motivation: Noise trader risk is a pervasive risk in the world's stock markets. It is driven by emotions and run counter to market stability. Noise trading has its practical repercussions. Hence, it is imperative for policymakers and investors to understand the behaviour and causes of noise risk to enhance market efficiency and optimize the financial decision-making process. Although most studies have confirmed the existence of noise in China's stock market, the volatility response findings have been mixed. Besides, prior studies found that China's stock market's volatility response behaves differently from its Western counterparts. Idea: In an attempt to examine the asymmetrical volatility response over different market conditions, we build our study on Feng et al. (2014) but over a different market sentiment period. Additionally, we combine our quantitative research with qualitative analysis. Hence, our paper verifies the existence of noise trading in China's stock market and dissects the plausible rationales behind the findings, keeping China’s unique historical developments and market conditions in mind. Data: Our sample data comprises the daily Shanghai Stock Exchange (SHSE) A-share index between 2nd January 2014 to 1 st July 2019. Methods: We first employ a variance ratio method to test for noise trading evidence and subsequently develop an EGARCH-M model to detect yield asymmetry in the SHSE A-share market. Findings: Our result suggests that noise trading is prevalent in China's stock market and that market returns are more volatile in the face of good news than bad news. Hence, our findings are similar to Chen and Huang (2002) but contradict Feng et al. (2014). We attribute our findings to the investor's irrational investment psychology and behaviour, such as the widespread "catch up and kill down" operations among the noise traders and the market’s deficiencies. Contributions: Hence, our results provide important indications to investors and policymakers to assess the market conditions and devise optimal strategies.
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Copyright (c) 2021 Liang Ye, Yeng-May Tan (Author)

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