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The purpose of the study is to check whether Indian high net worth individual (HNI) investors are suffering from overconfidence bias in personal life and in-stock investment approach. The study is to benchmark an ideal behaviour that an investor should exhibit under the overconfidence bias.

Both qualitative and quantitative methods were used to study the Indian HNI investors with overconfidence bias. As a first step, an exploratory study was conducted to identify the variables to define overconfidence bias. An extensive literature review along with in-depth interviews was conducted amongst investors, fund managers and the subject experts to check the content validity of the variables. The survey instrument was designed based on the objective of the study and theoretical framework. Both descriptive and inferential statistical tools such as the Z proportion test, logistic regression and structural equation model were applied to test the hypotheses.

It was found that there is a moderate impact of overconfidence bias amongst the investors both in normal life and whilst making investments in stock. This study found the influence of overconfidence bias in stock investment with respect to forecasting of the stock price movements, overtrading, overanalysis and overreaction.

This paper will help in understanding the Indian HNI investors’ behaviour under the impact of overconfidence bias. There is an empirical study to understand the implication of overconfidence bias on stock investors specifically for the HNI investors.

This study gives an insight into the fund managers to understand the Indian HNI investment behaviour. It is also helpful for HNI investors to understand and correct their behavioural biases related to overconfidence.

This paper will guide investors to understand the symptoms and repercussions of overconfidence bias in stock investment. They can also realize the subtle impact of overconfidence bias in personal and professional life, thus preventing them from making losses.

This work is the extension of the works of Terrace Odean on behavioural finance in the Indian Stock Investors' context. The concept of overconfidence bias and its implications of finance were developed by Kahneman and Tversky, and later by other behavioural finance researchers such as Malmendier, Hirshleifer, DeBondt, Odean, Barber, Shefrin and others. This paper studies stock investing behaviour with specific reference to Indian HNI investors.

The purpose of this paper is to estimate the direct effects of foreign direct investment (FDI) on domestic target firms’ profitability gains, in India, post-acquisition. In particular, it focuses on identifying the importance of firms’ heterogeneities on the effects, taking into account the source of FDI, the intensity of firm interaction, and the target firms’ technology-absorptive capacity. Most importantly, the paper investigates whether the estimates depend on a combined rather than single impact of these heterogeneities.

To control for the possibility of selection bias and endogeneity, this empirical analysis uses a methodology that combines propensity score matching and difference-in-differences (PSM–DID) in adopting a comprehensive data set of both foreign- and Indian-acquired firms that were purchased through mergers and acquisitions in India between 1991 and 2013.

The analysis reveals four major findings. First, overall, the post-foreign acquisition target firms’ performance gains were positive and varied by the heterogeneous technology transfer capacity of the foreign investor. Second, it is possible that target firms located in industrial clusters with more foreign agglomeration experienced larger profitability gains through more dynamic firm interactions in terms of spillovers. Third, Indian targets with higher technology-absorptive capacity benefitted in higher profitability gains from acquiring and assimilating the superior technology that is transferred from foreign investors. Finally, an optimal combination of Indian target firms with higher technology-absorptive capacity and foreign investors with higher technology transfer capacity maximizes profitability gains, post-acquisition. This synergy effect is particularly prominent in clusters where more foreign firms agglomerate.

This study captures the true direct effect of FDI by adjusting the combined causal effects of various inherent heterogeneities in the target firms’ performance, thus correcting any possible bias, which few previous studies have addressed.

India is an emerging economy and one of the preferred investment destinations for environmental, social and governance (ESG) fund issuers. Institutional investors invest retail investors’ money, and hence, it becomes imperative for ESG fund managers to understand the social investment preferences of retail investors. This study aims to compare the Indian socially responsible (SR) investors and conventional investors in terms of their socially responsible investment (SRI) awareness level, opinions about broad and specific ESG issues, investment behavior and demographics. In addition, this paper makes an attempt to have a deeper insight into Indian investors’ behavior toward SRI by segmenting the Indian retail investors based on their SRI awareness level, attitude toward ESG issues and intention to accept lower financial returns, and choices made by them as consumers.

After collecting the data through the survey method an independent t-test is used to compare SR investors with conventional investors. Chi-square has been used to analyze the data related to demographics, and cluster analysis is used to identify segments among Indian retail investors.

The results indicated that Indian SR investors’ SRI awareness level is more, they are more concerned about broad and specific ESG issues, they are more into faith-based investing, and are responsible consumers vis-à-vis conventional investors. As per demographic, SR investors are in the middle age group of 30–40 years, male, hold a postgraduate degree and have an annual income of 10–20 lakhs in comparison to conventional investors. The results of cluster analysis indicated that Indian retail investors can be classified into three groups based on their SRI awareness, intention to sacrifice financial return, attitude toward ESG issues and choices made by them as consumers.

Results have implications for national and international fund managers, policymakers, regulators and society. These results will help mutual fund companies to provide curated SR mutual funds as per the behavior and choice of retail investors and penetrate the Indian investment market more deeply.

This research study contributes to the literature on SRI by identifying the differentiating characteristics of Indian SR and conventional investors and segmenting Indian retail investors on the basis of their SRI awareness, the importance of ESG issues and choices made by them as investors and consumers.

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 determinants of investor sentiment based on stock market proxies are found in numbers in empirical studies. However, investor sentiment antecedents developed from primary survey measures by constructing an investor sentiment index (ISI) are not done till date. The purpose of this paper is to fill this research gap by first developing an ISI for the Indian retail investors and then examining the investor-specific, stock market-specific, macroeconomic and policy-specific factors’ individual impact on the investor sentiment.

First, the authors develop the ISI by using the mean scores of six statements as formulated based on popular direct investor sentiment surveys undertaken throughout the world. Then, the authors employ the structural equation modeling approach on the responses of 576 respondents on 40 statements (representing the index and four study hypotheses) collected in 2016 across the country.

The results show that investor- and stock market-specific factors are the major antecedents of investor sentiment for these investors. However, interestingly macroeconomic fundamentals and policy-specific factors have no role to play in driving their sentiment to invest in the stock market.

The major implication of the results is that the Indian retail investors are showing a mixed approach of Bayesian and behavioral finance decision making. So, these implications can guide the investment consultants, regulators, other stakeholders in markets and overwhelmingly the retail investors to introspect their investment decision making across time horizons.

The formulation of ISI in an emerging market context and thereafter examining possible antecedents to influence retail investors in their investment decision making are not done till date. So, the study is unique in its research issue and findings and will have significant implication for the retail investors at least in emerging market contexts.

The purpose of this paper is to develop an in-depth contextualized understanding of individual investors’ buying decision in Indian stock market. Specifically, it provides answers to: how do individual investors make buying decision in stock market; and how and when do biases set in during such decisions. The paper also brings forward some aspects of individual’s journey as an investor.

Given the exploratory nature of this study, the paper takes a step away from typically used variance approach and instead uses a process approach. The authors do in-depth one-on-one interview, where each respondent shares his/her lived experiences as an investor retrospectively. To understand buying decision, each respondent is asked to elaborate three significant buying transactions carried out by him/ her in stock market.

Socio-cultural factors are found to have significant influence in inducing respondents to enter market. “Safe” vs “Risky” mental account emerges as the prominent stock categorization done by Indian investors. Three building blocks, namely, Identification, Rationalization and Further Validation emerge as the building blocks that culminate into buying decision of individual investors. The biases are seen to play a dual role in such decisions; as Attention Boosters and Rationales.

This study, to the best of authors’ knowledge, is first of its kind which amalgamates behavioral biases with phenomenon such as attention and Rationalization, to understand “how” behavioral biases set in during buying decision of individual investors.

The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms.

This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes.

Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors.

Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market.

This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner.

In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems.

This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

The study investigates the amplitude and direction of the movement of information between spot and futures indices. The study progresses to account for the investor's heterogeneity and compare the evolving structure of investors in emerging and developed economies. Further, the structural linkages in terms of returns and variance have been explored for the futures indices to contribute to meteor shower literature as explained by Engle et al. (1990); Yarovaya et al. (2017).

To facilitate the purpose, the Indian and Chinese markets were selected to represent emerging economies and the United States for developed one. The bivariate wavelet cum BEKK-GARCH (1,1) model was estimated.

For the developed markets, like the United States, the spot market improves its information transmission role with time horizon while exactly opposite holds for the Chinese market. A bidirectional overnight information spillover was found for all three pairs. The Indian futures market was vulnerable to bad news from the other two markets. Evidence suggesting the dominance of institutional investors in the Chinese futures market and retail investors in the Indian futures market is found.

The spot–futures relation has been studied on both the time and frequency domains considering different investment horizons. Due consideration has been taken to account for the overlapping trading hours.

The purpose of this study is to examine the role of personality traits (PTs) of individual investors on their investment intention (II). Further, to study the mediating role of overconfidence (OC) bias and financial literacy (FL) on the relationship between PTs and II.

The present study uses the quantitative approach for the data collection from the sample of 327 Indian investors investing in the stock market. The questionnaire was divided into segments to assess the investor’s PTs, OC, FL and II. The PT has been measured using the Big Five Personality Traits. Confirmatory factor analysis was used to test the reliability and validity of the constructs. The hypothesis was tested using structural equation modeling.

Findings of the study show that the PTs of an individual investor are associated with FL and II but insignificant with OC bias. Further, the FL and OC bias have a positive and significant influence on II. In addition, the mediation analysis showed that FL partly mediates the relationship between PTs and II.

The present study is helpful for financial companies, government, personal finance advisors and individual investors; they can keep in mind the behavior-related traits that can influence the investment decisions and design the portfolio accordingly. The policy-makers can implement programs on FL to enhance investment decisions in India.

This paper is unique that covers the mediating role of psychological bias, i.e. OC bias and FL, between the PTs and II of an Indian investor.

Millennials are a vital generational cohort of the Indian population, and understanding their motivation to participate in the stock market is crucial. This study aims to understand the investment decision-making behavior among millennials in the Indian Stock Market.

Using a cross-sectional research design that entails in-depth personal interviews, this study aims to understand the equity investment behavior of millennials. Verbatim texts from interview transcripts were used to analyze the content and arrive at themes.

The study investigated the motivation to enter the stock market and gained insights into how individuals make equity investment decisions considering economic and behavioral dimensions. The basis for stock selection was predominantly on the self-analysis of investors. Multiple stock selection priorities are also discussed. In addition, informants ensured asset diversification and exercised various strategies to overcome emotions. Furthermore, they suffered from various behavioral biases.

Individual investors are the least informed and most impacted stakeholders in the stock markets; therefore, this study contributes fresh insights to enhance their financial security. The paper also examines some noticeable behavioral tendencies retail investors exhibit and gathers helpful strategies for mitigating behavioral biases.

The uniqueness of the research lies in its adoption of a qualitative methodology that uses the investment experience of millennial investors to reveal the components of decision-making behavior and investor psychology. The findings are thereby unique and have significant managerial implications.