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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.

An important but neglected area of investigation in digital entrepreneurship is the combined role of both core and peripheral members of an emerging technological field in shaping the symbolic and social boundaries of the field. This is a serious gap as both categories of members play a distinct role in expanding the pool of resources of the field. I address this gap by exploring how membership category is related to funding decisions in the emerging field of artificial intelligence (AI).

The first quantitative study involved a sample of 1,315 AI-based startups which were founded in the period of 2011–2018 in the United States. In the second qualitative study, the author interviewed 32 members of the field (core members, peripheral members and investors) to define the boundaries of their respective role in shaping the social boundaries of the AI field.

The author finds that core members in the newly founded field of AI were more successful at attracting funding from investors than peripheral members and that size of the founding team, number of lead investors, number of patents and CEO approval were positively related to funding. In the second qualitative study, the author interviewed 30 members of the field (core members, peripheral members and investors) to define their respective role in shaping the social boundaries of the AI field.

This study is one of the first to build on the growing literature in emerging organizational fields to bring empirical evidence that investors adapt their funding strategy to membership categories (core and peripheral members) of a new technological field in their resource allocation decisions. Furthermore, I find that core and peripheral members claim distinct roles in their participation and contribution to the field in terms of technological developments, and that although core members attract more resources than peripheral members, both actors play a significant role in expanding the field’s social boundaries.

Core AI entrepreneurs who wish to attract funding may consider operating in fewer categories in order to be perceived as core members of the field, and thus focus their activities and limited resources to build internal AI capabilities. Entrepreneurs may invest early in filing a patent to signal their in-house AI capabilities to investors.

The social boundaries of an emerging technological field are shaped by a multitude of actors and not only the core members of the field. The author should pay attention to the role of each category of actors and build on their contributions to expand a promising field.

This paper is among the first to build on the growing literature in emerging organizational fields to study the resource acquisition strategies of entrepreneurs in a newly establishing technological field.

In this chapter, we are among the first to investigate the actual course of affairs in AGMs with respect to shareholder forum rights. In the first part of the chapter, we provide descriptive statistics on the use of the right to ask questions and speak in AGMs in the Netherlands. We find that in an average meeting there are around 42 questions and remarks made by around 8 shareholders. Most of these questions and remarks seem to be relevant; with a categorization framework of 14 topics, we could already identify over 50% of these questions and remarks. However, we also find that the average number of shareholders that physically ask questions is only 8. Next, we consider the determinants of the use of these forum rights. In several panel data analyses with a Poisson distribution and a negative binomial distribution, we, inter alia, found that the ‘importance of the meeting’ generally contributes to the amount of questions and remarks and the number of shareholders that actively engage in discussions. We have also found that the number of speakers – and the number of private investors – that actively attend the AGM depends on previous attendance numbers. This may imply that there is a small base of very active (private) investors in the Netherlands. We conclude that the forum function of AGMs is definitely relevant, but given the low number of shareholders that make use of these rights, amendments may be considered.

The purpose of this paper is to study the reallocation of initial public offering (IPO) shares to retail investors, non-institutional buyers (NIBs) and qualified institutional buyers (QIBs). The authors examine how the reallocation process is related to the pricing decision of the underwriter. The authors also examine the long-run performance of the IPOs classified on the basis of the highest reallocation by retail investors, NIBs and QIBs.

The authors use regression analysis as well as 2SLS and three-stage least squares models to test the hypotheses. For long-run performance analysis, the authors adopt Carhart’s (1997) four-factor model.

First, the authors provide evidence that the reallocation of IPO shares for retail investors, NIBs and QIBs is frequent. Second, all three categories of investors are treated differently in the reallocation of underpriced shares. Third, the authors find that the reallocation and pricing strategies are interdependent and both the strategies are used by the underwriter to reward and favor retail investors for showing high level of demand. The authors find that in India, underwriters reward retail investors. Lastly, even though underwriters favor retail investors for reallocation, the authors find that IPOs which receive highest reallocation to retail investors perform poorly in the long run.

This paper is the first paper to show evidence of reallocation of IPO shares by underwriters for an emerging market. The paper is different from other papers as the regulatory regime present in the Indian markets is different from other markets.

This research mainly intends to ascertain the stimulus of investor investment tendencies on the amount of capital investment in the share market.

Utilizing a sample of 477 individual investors who actively trade on the Bangladesh capital market, this empirical study was conducted. The objective of this examination is to ascertain the investment trading behavior of retail investors in the Bangladesh capital market using multiple regression, hypothesis testing and correlation analysis.

The coefficients of market categories, preferred share price ranges and investment source reveal negative predictor correlations; all predictors are statistically significant, with the exception of investment source. Positive predictive correlations exist between investor category, financial literacy degree, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment selection. Except for risk consideration and investment monitoring activities, all components have statistically significant predictions. The quantity of capital invested in the stock market is heavily influenced by the investment duration, preferred share price ranges, investor type, emotional toleration level and decision-making accuracy level.

This investigation was conducted exclusively with Bangladeshi individual stockholders. Therefore, the existing study can be extended to institutional investors and conceivably to other divisions. It is possible to conduct this similar study internationally. And the query can enlarge with more sample size and use a more sophisticated econometric model. Despite that the outcomes of this study help the regulatory authorities to arrange more informative seminars and consciousness programs.

The conclusions have practical implications since they empower investors to modify their portfolios based on elements including share price ranges, investment horizons and emotional stability. To improve chances of success and reach financial objectives, they stress the significance of bettering financial understanding, active monitoring and risk analysis. Results can also be enhanced by distributing ownership over a number of market sectors and price points. The results highlight the value of patience and giving potential returns enough time.

This study on the trading behavior of investors in Bangladesh is unique and based on field study, and the findings of this study will deliver information to the stakeholders of the capital market regarding the investors’ trading behavior belonging to different categories, financial literacy level, investment duration, emotional tolerance level and internal feeling.

The purpose of this study is to examine whether the influence of block ownership on firm performance depends on the identity of the largest investor.

The authors analyse the data for New Zealand companies for the period from 2002 to 2007 and develop multiple regression models which test the influence of block ownership on firm performance subject to the identity of the investor. A two‐stage least square approach is employed to test the effect of possible reverse causality between block ownership and firm performance on the relationship found in multiple regression models.

The authors find that the concentrated ownership has a positive, albeit decreasing, association with firm performance. This relationship is conditioned on the identity of the largest investor. Those companies whose block investors were financial institutions performed better than their peers. The superior influence of financial investors on corporate performance did not disappear even when the endogeneity of this relationship was accounted for.

The main contribution of this paper is the finding of a differential influence of various identities of block investors on firm performance. It questions the role that some domestic block investors play in the governance of New Zealand companies and the reason why the financial system has allowed corporate entities to be the main shareholders of the majority of firms when they underperform relative to their peers.

The economic system is an expectation's feedback system, thus decisions made by economic agents are based on their expectations about the future state of the economy. These decisions affect actual realization of economic variables and this process leads to the new expectations. For a long period of time, economics was based on the erroneous belief that economic agents apply rational calculations to economic and financial decisions. The main purpose of the current paper is to present the theoretical model explaining emotion's component of expectations in the process of financial decision making.

The research is based on the generally accepted scientific qualitative and quantitative methods, including monographic method.

The paper shows how the expectations and subjective beliefs of different financial market participants could be translated into prices. After describing the main investor's categories, it is possible to model their subjective beliefs about the current price evolution on the stock exchange and formulate the demand strategy of each investor's group. Finally, the model shows mathematical considerations how prices result from demands, considering that they are set by the market maker.

The paper shows how emotions impact investors' beliefs and could be transmitted into prices. A particular agent category – the emotional investor – was formulated, who exclusively follows his intuition and whose presence influences market prices. So, there is no doubt that an appropriate rational strategy requires the adoption to the new kind of market agent and theoretical considerations presented in the paper could contribute to this process.

The purpose of this paper is to examine the presence the behavioral biases in Indian investors specifically, overconfidence, excessive optimism (pessimism), herd behavior and the disposition effect. It further investigates the role of demographics and investor sophistication in influencing the biases. Finally, it reveals which bias is most prevalent in the Indian context.

For this purpose, a survey has been conducted on the investors of the Delhi/NCR area. The data have been collected with the help of a structured questionnaire that is analyzed with the help of relevant statistical tools.

The survey evidence shows that behavioral biases are dependent on investors’ demographics and their trading sophistication with highest influencing factors being age, profession and trading frequency. Each bias corresponds to a specific set of investor characteristics and overconfidence comes out to be the most important bias in the Indian context.

The potential limitations of the present survey can be ascribed to socially desirable responses and their difference with actual market behavior. Further, due to time and resource constraint, the data set is limited to investors of only Delhi/NCR.

This study is most relevant for financial advisors, as it facilitates them in gaining a better understanding of their clients’ psychology. It can aid them in developing behaviorally modified portfolio, which best suits their clients’ predisposition.

The paper gives a unique insight on the investors’ profile corresponding to each bias under consideration. It not only updates the evidence on behavioral biases but also highlights which bias is the most influential in the Indian context.

The unique regulatory design of India provides us with the opportunity to disaggregate traditional initial public offering (IPO) underpricing into three categories: voluntary, pre-market and post-market. The presence of anchor investors in India makes it a compelling case to study. These individuals were introduced to bring transparency in the book building process, but their impact on pre-market and post-market underpricing was not foreseen. Therefore, the purpose of this paper is to evaluate the impact of anchor investors on the IPO underpricing after disaggregation and on the long-run performance of an IPO.

A sample covering 232 IPOs from a period of 2009–2018 is included. The empirical analysis explores the impact of various firm-specific as well as market-specific variables on IPO underpricing. The financial data for the empirical analysis are extracted from Prime database and websites of National Stock Exchange and Bombay Stock Exchange. To deal with the outliers effectively, this paper deploys “robust-regression.”

The study finds that investor’s subscription rate and voluntary underpricing impacts the pre-market but do not have any impact on the post-market while the age of the firm has a different impact on both the markets and the number of anchor investors have the same impact in both markets. Anchor investors’ participation increases the pre-market as well as post-market underpricing. Lastly, the long-term performance of IPOs backed by the anchor investors is high relative to the IPOs not subscribed to by the anchor investors.

This paper is believed to be the first attempt to study the impact of anchor investors on the disaggregated IPO underpricing. The findings of this study will have a great insight for the investors.

This study identifies the factors responsible for obtaining price premium on privately placed equity in a developing market.

We examine a unique data set of a special case of private placement of equity, Qualified Institutional Placement (QIP) in India purchased at a premium. The study analyzed 188 equity issues offered between September 2006 and December 2014. On average, we find that QIP issues received a price premium of 4.38%. The study employed binary probit and ordinary least square regression models to analyze the probability and magnitude of the premium.

The study attributes the price premium of QIP to certification effect through group affiliation, signaling through promoters' ownership and monitoring effect through existing institutional investors. These factors influence the probability of premium for QIP issues. However, group affiliation and institutional ownership do not significantly influence the magnitude of the premium.

The private placement of equity is usually offered at a discount. Our findings contribute to the existing literature by evaluating the premium obtained on private placement as a unique scenario in emerging market supported through certification hypothesis, monitoring hypothesis and signaling.