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In 1994, Shefrin and Statman defined two different traders in equity market. They are information trader and noise trader. Information trader is defined as an individual who form expectations on the basis of https://www.51lunwen.org/information and trade on those expectations. Information traders are a very difficult choice to play, meant only for the very social and crafty individual who can obtain secrets from either side of a conflict and then sell that information at high cost and hopeful without getting a bounty placed on one’s head. The other trader is noise trader. In general, noise traders are those agents who trade stocks without any specific information of the shares.
Both information trader and noise trader may make mistake, and these mistake will cause behavioral error. In general, information traders may well correct the pricing errors introduced by noise traders, but sometimes, information traders may undercorrect or overcorrect noise errors.

Black (1986), Odean (1998), De Long, Shleifer, Summers and Waldman (DSSW) (1990) demonstrated the survival of the “second driver”. According to Black’s (1986) definition of noise traders, they are “traders that trade on noise as if it were information”. Fama (1965) developed the efficient market hypothesis (EMH), which asserts that financial market are “informationally efficient” and the price of traded assets reflects it intrinsic value and available information. Fama and Friedman thought that the expected return of market for noise traders was always negative, and their financial situation was always deficit. So, they couldn’t stay a long time. On the other hand, in the behavioural finance theory, the latest research results have proposed the opposite point of view, De Long, Shleifer, Summers and Waldman (1990) proposed DSSW model demonstrates that the noise traders can obtain a positive expected return. So far, De Long (1991) established portfolio allocation model and Kogan model (2003) illustrates the noise traders’ long-term viability. Moreover, DSSW model can measure noise trader risk that can be applied in different markets.
To date the literature has forced on some countries’ stock market, such as Australia and USA, however there is no research on the effects of noise traders on the Chinese stock market. Chinese stock still have noise traders and still have volatility and inefficiencies. Behavioural finance plays an important role in stock market like Australia and USA. From some studies, it is difficult to draw a definitive conclusion regarding whether China’s stock market is efficient or not. Song and Jin (1995) determine that the Shanghai stock exchange has already been weakly efficient. However Zhang and Zhou (2001) conclude that China’s stock market has not achieved weak-form efficiency.
Information adjusted noise model (IANM) provide a measure of noise traders. This model shows the interactions between noise traders and information traders. I will apply this model in the Chinese stock market. The Chinese stock market is composed of three securities markets: the shanghai stock exchange, the Shenzhen stock exchange and the Hangsheng (Hong Kong stock exchange). There are two types of shares, A-share and B-share with A share having restricted ownership to Chinese citizens only and B share being open to all market participants.
In the first step, they compute the behavioural beta and the traditional CAPM beta. The difference 本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。