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This comprehensive study aims to take a punctilious approach intended to present qualitative and quantitative knowledge on the emerging concept of noise trading and identify the emerging themes associated with noise trading.

This study combines bibliometric and content analysis to review 350 publications from top-ranked journals published from 1986 to 2020.

The bibliometric and content analysis identified three major themes: the impact of noise traders on the functioning of the stock market, traits of noise traders and different proxies used to measure the impact of noise trading.

This study undertakes research papers related to the field of finance, published in peer-reviewed journals and that too in the English language.

This study shall accommodate rational traders, portfolio consultants and other investors to gain deeper insights into the functioning of noise traders. This will further help them to formulate their trading/investment strategies accordingly.

The successful combination of the bibliometric and content analysis revealed major gaps in the literature and provided future research directions.

The purpose of this paper is to: first, test if information-adjusted noise model (IANM) can be applied in China; second, quantify noise trader risk, overreaction, underreaction and information pricing errors in that market; and third, explain the relationship between noise trader risk and return.

The authors use a behavioural asset pricing model (BAPM), CAPM, the information-adjusted noise model and model proposed by Ramiah and Davidson (2010).

The findings show that noise traders are active 99.7 per cent of the time on the Shenzhen A-share market. Furthermore, our results suggest that the Shenzhen market overreacts 41 per cent of the time, underreacts 18 per cent of the time and information pricing errors occur 40 per cent of the time.

Various methods have been applied to the Chinese stock market in an effort to measure noise trading activities and all of them failed to account for information arrival. Our study uses a superior and alternative model to detect noise trader risk, overreaction and underreaction in China.

The purpose of this paper is to research and analyze the influence of institutional investors in the present securities market due to behavior alienation with “running after rising and falling” and “herd behavior”.

A DeLong, Shleifer, Summers, and Waldmann (DSSW) model with positive feedback trading is established first to show the trading process, and these securities prices are calculated considering the investors' emotion. Through numerical analysis, the influence of institutional investors on securities price fluctuation is simulated. Further, the analysis of institutional investors' incomes is processed based on this model.

Through these analyses, the following conclusions are drawn: it lies on the scale of positive feedback traders and their sensitivity to past market performances whether the institutional investors can stabilize the market, and it is not necessary for the institutional investors to benefit from manipulating the market due to the existence of noise trader risk, so the positive feedback traders may survive in the security market over the long term.

The DSSW model considering positive feedback trading, presented in the paper, is more effective in analyzing the relation among the behavior of institutional investors, securities pricing and securities price fluctuation. The paper proposes some advice for policy decisions, which is helpful for government and institutions to maintain the stability of securities markets.

The purpose of this paper is to examine the informative power of rating agencies in the process of establishing sovereign risk, over a ten‐year period (1997‐2006).

First, following an earlier model, the concept of noise‐rater risk is introduced. Second, four panels were carried out to identify the most significant macro factors in determination of sovereign ratings, taking into account contemporaneous and lagged variables. The dependent variable is sovereign rating issued at the end of each year. Third, three kinds of errors committed by rating agencies when altering the sovereign ratings of emerging countries are defined.

Noise‐rater risk amplifies the chances of noise traders obtaining higher returns than arbitrators. The panels show that, with the exception of debt, all other factors are sample dependant, and that variables and samples leave ample space for subjective factors. Analysis of errors demonstrates that rating agencies appear to lose their focus/modus operandi/principles in times of crisis, and that they commit more errors immediately prior and after the onset of a financial crisis.

The paper argues for a cautious analysis of rating agency's informative power. Like any other stakeholder, rating agencies are influenced by cognitive limitations, erroneous beliefs, and the cost of acquiring and using information.

The paper uses behavioral finance methodologies to observe rating agencies and demonstrates, from its observations of sovereign ratings, that agencies tend to fail at times of financial turmoil, i.e. when they are most needed, by abandoning their “look at the future” principle.

The purpose of this paper is to examine the long-run survival of earnings fixated traders.

This paper builds a theoretical model of a competitive securities market where both rational traders and earnings fixated traders receive an informational signal about the asset payoff before any trade occurs. Since earnings fixated traders underestimate the mean and variance of the risky asset payoff, earnings fixated traders is shown to make less expected profits than rational traders.

If traders’ types replicate according to the relative profitability of their trading strategies, then earnings fixated traders will disappear in the long run. The results of this paper provide analytical support to Tinic’s (1990) intuition about the eventual disappearance of earnings fixated traders.

In the literature, the underestimation of risk is popularly viewed as the cause of irrational traders being better able to exploit the misvaluations (created by noise traders) than rational traders. Hence, it favors the survival of irrational traders over rational traders. However, this paper disapproves this intuition in the informational environment of the competitive securities market.

The market environment plays a crucial role in determining the long-run survival of irrational traders.

This paper is the first to present a theoretical result showing that in this informational environment of the competitive securities market, the underestimation of risk by irrational traders does not give them advantage over rational traders in exploiting the misvaluations (created by noise traders) as it does in Callen and Luo (2011) and Hirshleifer and Luo (2001).

The purpose of this paper is to investigate the impact of individual investor sentiment on the return process and conditional volatility of three main US market indices (Dow Jones Industrial Average, S&P500 and Nasdaq100). Individual investor sentiment is measured by aggregate money flows in and out of domestically oriented US mutual funds.

A generalised autoregressive conditional heteroscedasticity (GARCH)‐in‐mean specification is used, where our measure for individual sentiment enters the mean and conditional volatility equation.

For a sample period of six years (February 1998 until December 2004), we find that sentiment has a significant and asymmetric impact on volatility, increasing it more when sentiment is bearish. Using terminology of De Long et al., we find evidence for the “hold more” effect, which states that when noise traders hold more of the asset, they also see their returns increase, and the “create space” effect, which states that noise traders are rewarded for the additional risk they generate themselves.

In contrast to existing studies using explicit measures of market sentiment on low sampling frequencies, the use of daily mutual flow data offers a unique picture on investors' portfolio rebalancing and trading behavior. We propose an integrated framework that jointly tests for the effects of mutual fund flows on stock return and conditional volatility.

The purpose of this paper is to examine proposals for a Tobin tax to curb currency speculation in global markets.

Financial markets are viewed from the perspective of Michel Serres.

Managing volatility is really about managing relationships that can buffer governments against risk. The resolution of a paradox is embracing the paradox.

The work of Michel Serres has not previously been used in analyses of global currency markets. His theory of parasitical relationships offers a novel response to proposals for a Tobin tax.

The purpose of this paper is to analyze the trading behaviors of retail investors and investigate their impacts on stock returns.

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.

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.

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.

The purpose of this paper is to comprehensively review a large and heterogeneous body of academic literature on investors' feedback trading, one of the most popular trading patterns observed historically in financial markets. Specifically, the authors aim to synthesize the diverse theoretical approaches to feedback trading in order to provide a detailed discussion of its various determinants, and to systematically review the empirical literature across various asset classes to gauge whether their feedback trading entails discernible patterns and the determinants that motivate them.

Given the high degree of heterogeneity of both theoretical and empirical approaches, the authors adopt a semi-systematic type of approach to review the feedback trading literature, inspired by the RAMESES protocol for meta-narrative reviews. The final sample consists of 243 papers covering diverse asset classes, investor types and geographies.

The authors find feedback trading to be very widely observed over time and across markets internationally. Institutional investors engage in feedback trading in a herd-like manner, and most noticeably in small domestic stocks and emerging markets. Regulatory changes and financial crises affect the intensity of their feedback trades. Retail investors are mostly contrarian and underperform their institutional counterparts, while the latter's trades can be often motivated by market sentiment.

The authors provide a detailed overview of various possible theoretical determinants, both behavioural and non-behavioural, of feedback trading, as well as a comprehensive overview and synthesis of the empirical literature. The authors also propose a series of possible directions for future research.