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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 examine whether the futures volatility could affect the investor behavior and what trading strategy different investors could adopt when they meet different information conditions.

This study introduces a two‐period overlapping generation model (OLG) model into the future market and set the investor behavior model based on the future contract price, which can also be extended to complete and incomplete information. It provides the equilibrium solution and uses cuprum tick data in SHFE to conduct the empirical analysis.

The two‐period OLG model based on the future market is consistent with the practical situation; second, the sufficient information investors such as institutional adopt reversal trading patterns generally; last, the insufficient information investors such as individual investors adopt momentum trading patterns in general.

Investor trading behavior is always an important issue in the behavioral finance and market supervision, but the related research is scarce.

The conclusion shows that the investors' behavior in Chinese future market is different from the Chinese stock market.

This study empirically analyzes and verifies the different types of trading strategies investors could; investors such as institutional ones adopt reversal trading patterns generally; while investors such as individual investors adopt momentum trading patterns in general.

The purpose of this paper is to investigate who trade actively in the Malaysian stock market and what determines investors’ active trading decisions.

Using a cross-sectional survey on individual investors, the study identifies active and inactive investors and then, investigates active trading by estimating binary logistic regression.

Active investors in Malaysia are more likely to be male, working in non-finance-related sectors and are more experienced. The likelihood of active trading increases with the number of hours spent on researching investment, very short-term favorable unemployment and economic growth expectations (three-month) and past investment outcomes, whereas this probability decreases with higher cognitive ability and short-term unemployment expectations.

The results imply that regulators may focus on certain groups of investors, based on the result of this study, and provide them training to reduce inactivity in this market. As active trading in response to past investment outcomes indicate rational response, regulators therefore may inform investors to learn about their ability and skill from their prior investment outcome, through educational program. Educational program may also include the role of macroeconomic indicators in active investing decisions.

This is the first study to combine a list of demographic and socio-economic characteristics, investment characteristics, macroeconomic expectations and past investment outcomes together to explain the likelihood of active trading.

The purpose of this paper is to investigate if earnings management affects the trades of different investors prior to earnings announcements.

Using a unique account-level trading data set from the Chinese stock market, the author investigates the different investor trading patterns prior to earnings announcements.

The author obtains direct evidence to show that: first, institutional investors, particularly active ones, tend to sell (buy) stocks before negative (positive) earnings surprises; second, institutional investors buy stocks intensively with the lowest earnings management and the highest earnings surprises, and the trading patterns are primarily driven by active institutions. No significant trading pattern is observed on the stocks with negative earnings surprises; and third, the author uses a natural experiment in accordance with the Chinese accounting standards reform to address endogeneity, and the causality of the results still holds.

The findings provide clear evidence by emphasizing the importance of earnings management in the formulation of investor decisions.

This study examines the role of behavioural factors, such as confidence, optimism, pessimism and rational expectation, in affecting investment decisions in the Pakistani stock market.

Using daily trading data of Karachi Stock Exchange-100 index from January 2012 to December 2015, different regression models, including descriptive statistics and stationarity tests, are performed.

Results indicate that stock market trading has suffered from pessimistic behaviour of investors. In the first model, the authors find a positive sign of confidence and negative sign of optimism with the trading volume. The second model shows a positive role of confidence and rational expectations in affecting the trading volume in daily, Monday and Friday samples. The results of the third model show a negative sign of both optimism and rational expectation with the trading volume. Furthermore, the next model shows a negative sign of confidence combined with pessimism while testing their relationship with the trading volume. Finally, results of the final model suggest that optimism negatively affects the trading volume, and on the other hand, pessimism has a positive impact on the trading volume.

The method and empirical testing of behavioural biases and their relationship with economic variable used in this study seem to be a promising way to better understand the role of psychology in deriving financial decisions for academics and policymakers.

This study uses secondary data for measuring behavioural biases and decomposes the effect between rational expectation and behavioural biases.

Several studies have observed that stocks tend to drop by an amount that is less than the dividend on the ex-dividend day, the so-called ex-dividend day anomaly. However, there still remains a lack of consensus for a single explanation of this anomaly. Different from other studies, this dissertation attempts to answer the primary research question: how can investors make trading profits from the ex-dividend day anomaly and how much can they earn? With this goal, I examine the economic motivations of equity investors through four main hypotheses identified in the anomaly's literature: the tax differential hypothesis, the short-term trading hypothesis, the tick size hypothesis, and the leverage hypothesis.

While the U.S. ex-dividend anomaly is well studied, I examine a long data window (1975–2010) of Thailand data. The unique structure of the Thai stock market allows me to assess all four main hypotheses proposed in the literature simultaneously. Although I extract the sample data from two data sources, I demonstrate that the combined data are consistently sampled. I further construct three trading strategies – “daily return,” “lag one daily return,” and “weekly return” – to alleviate the potential effect of irregular data observation.

I find that the ex-dividend day anomaly exists in Thailand, is governed by the tax differential, and is driven by short-term trading activities. That is, investors trade heavily around the ex-dividend day to reap the benefits of the tax differential. I find mixed results for the predictions of the tick size hypothesis and results that are inconsistent with the predictions of the leverage hypothesis.

I conclude that, on the Stock Exchange of Thailand, juristic and foreign investors can profitably buy stocks cum-dividend and sell them ex-dividend while local investors should engage in short sale transactions. On average, investors who employ the daily return strategy have earned significant abnormal return up to 0.15% (45.66% annualized rate) and up to 0.17% (50.99% annualized rate) for the lag one daily return strategy. Investors can also make a trading profit by conducting the weekly return strategy and earn up to 0.59% (35.67% annualized rate), on average.

The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of Thailand (SET) has granted Thai stock brokers permission to develop and offer their customers algorithm and automatic stock trading. However, algorithm trading on SET was not widely adopted. This chapter intends to design and empirically estimate a model in explaining Thai investors’ acceptance of algorithm trading. The theoretical framework is based on the theory of reasoned action and technology acceptance model (TAM). A sample of 400 investors who have used online stock trading and 300 investors who have used algorithm stock trading were observed and analyzed using structural equations model (SEM) and generalized linear regression model (GLM) with a Logit specification. The results confirm that attitudes, subjective norm, perceived risks, and trust toward algorithm stock trading are factors determining investors’ behavior and acceptance of using algorithm stock trading. Investor’s perception and trust on algorithm stock trading as a trading strategy is a major factor in determining their perceived behavior and control, which affect their decision on whether to invest using algorithm trading. Accordingly, it can be concluded that Thai investors is willing to accept algorithm trading as a new financial technology, but still has concern about the reliability and profitable of this new stock trading strategy. Therefore, algorithm trading can be promoted by building investors’ trust on algorithm trading as a reliable and profitable trading strategy.

The main thrust of the present study is to look into the trading patterns of behavior and investment performance exhibited by individual and institutional investor categories in the Qatar Exchange (QE). The paper aims to discuss these issues.

The present study uses daily aggregated investment flows made separately by each investor group, as well as daily closing price observations of the QE stock composite index. The trading patterns of investor categories are examined by estimating a bivariate vector autoregressive process of order p, VAR (p). To determine whether each category performs well or poorly over the entire sample period, each investor category's cumulative returns are estimated and analyzed.

The empirical results reveal that institutional investors pursue positive feedback trading strategies, whereas individual investors tend to be negative feedback traders. Both investor categories appear to be engaged in herding behavior. Additionally, institutional investors perform well over almost the entire sample period. In contrast, individual investors' negative market timing ability dominates their overall poor performance.

The investment performance gap found between institutional investors and individual investors in the Qatari capital market may reflect a large information asymmetry in favour of the former category. Indeed, the poor performance of individual investors implies that their trading activities are generally driven by factors and considerations that are irrelevant to fundamentals. Moreover, their irrational trading decisions may play some role in the formation of asset price bubbles.

The present study makes the first attempt to provide empirical evidence on the investment patterns and performance of individual and institutional investors trading on the Qatari capital market.

This analysis is the first to explore the overall roles of the offsetting attraction and distraction influences of earnings news in shaping the level of attention given to the equity market by market participants.

We use multivariate regression approach and examine how trading activity levels within the set of non-announcing firms varies with respect to collective measures of contemporaneous earnings announcement visibility. We employ attention and information transfer theories in our hypothesis development.

This analysis is the first to explore the overall roles of the offsetting attraction and distraction influences of earnings news in shaping the level of attention given to the equity market by market participants. Specifically, we examine how the number of earnings announcement activity affects investor attention as measured by trading volume given to the set of non-announcing firms. We find that while earnings announcement numbers lower trading volume responses to earnings news among announcing firms (consistent with Hirshleifer et al., 2009), their distractive influence does not carry over into the market as a whole. More importantly, investor attention to both the overall market and the larger subset of non-announcing firms increase in response to earnings news activity levels. However, after decomposing the announcers as same-industry and different-industry announcers, we find that investor attention to the non-announcing segment of the market increases with the number of same-industry announcers, but actually seems to decrease (i.e. they distract attention) with the number of different-industry announcers. We also find that the associated earnings surprise brings attention to non-announcing firms (consistent with earnings news is relevant to overall market price movements). Finally, we find that distraction effects are attenuated in the financial crisis period.

A promising area of future research is to examine the relation between market pricing efficiency and aggregate earnings activity for the set of non-announcing firms. Although it will be a challenging task to measure pricing efficiency for the non-announcers, this will complement the prior literature only focusing on the announcing segment of the market.

First, instead of assessing the impact of number of earnings announcements on the subset of announcing firms, which is a micro-level perspective, we identify the impact of news arrivals on all firms in the market including the vastly larger set of non-announcing firms. Second, by decomposing the number of announcements into industry-related and -unrelated news we show that different types of news arrivals spark investor attention differently, suggesting the importance of categorizing the news into related and unrelated industries.

A potential future area of research identified by our analysis is to investigate what type of investors' attention is distracted or attracted during the earnings announcements. A promising area of future research is to examine the relation between market pricing efficiency and aggregate earnings activity for the set of non-announcing firms.

This paper is the first one exploring the overall roles of the offsetting attraction and distraction influences of earnings announcements in shaping the level of investor attention given to the equity market by market participants. Our findings should be of interest to investors, analysts, security market regulators and researchers.

Extending the extant literature and using Qatar’s equity market as a case study, this paper aims to look into the potential impacts of foreign investor groups’ trading activities on market volatility in comparison with those of Qatar’s domestic investor counterparts.

The dataset is comprised of daily aggregated values of stock purchases and sales made separately by four investor groups, namely, foreign individual investors, foreign institutional investors, domestic individual investors, and domestic institutional investors. An ex post measure of volatility introduced by Rogers and Satchell (1991) is employed. Four proxies for investor trading are considered separately in the analysis. The objective of the study is empirically addressed in the context of the Generalized Method of Moments estimation technique.

In general, there exists substantial contemporaneous price impact associated with foreign equity investment in the Qatari capital market, despite the fact that foreigners’ buy and sell trades are not as large as those of their domestic counterparts. More specifically, foreign institutional sales (purchases) tend to increase (reduce) market volatility. Like those of foreign institutions, the sell trades by foreign individuals have a positive impact on volatility. On the other hand, domestic institutional purchases are significantly negatively related with market volatility, whereas the sell trades by the same category have no impact on volatility. Finally, surprises in foreigners’ trading volumes turn out to be responsible for adding to volatility.

Although a sudden reversal of foreign capital flows can pose a real threat to the stability of the Qatari capital market, such capital flows are deemed to be an indispensable vehicle for enhancing the liquidity and efficiency of the market. Accordingly, policy makers in Qatar should overhaul the current foreign investment legislation to make it even more streamlined and better suited to achieving the country’s strategic vision for the market. Foremost in these reforms is relaxing the stringent 25 percent foreign ownership restriction. Such a relaxation process is highly recommended to be phased in only gradually, in order to weigh its pros and cons. In this regard, the authorities concerned should consider embarking on a range of procedures intended to ward off the adverse ramifications of foreign capital outflows.

To the author’s best knowledge, no study about the impact of foreign equity flows on domestic markets has been so far conducted using trading data from the Qatari market. This work presents one such attempt.