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This study explores the variance in investor responses to the corporate social responsibility (CSR) performance of firms, as influenced by information sources and investor types.

This study applies a short-term event study and cross-sectional analysis with unique CSR datasets obtained from newspaper articles and the Dow Jones Sustainability Index.

Investor reactions are significantly shaped by their sources of information. Individual investors are found to predominantly respond to accessible news announcements, whereas institutional investors show heightened sensitivity to adverse news from both scrutinized sources. Foreign investors, mirroring institutional investors' patterns, uniquely react positively to index additions.

Investors’ assessment of CSR activities varies due to the differing sources of information obtained; further, it is affected by the type of investor.

The findings guide public relation managers in strategizing CSR communication toward diverse investor types. This includes recommending targeted approaches for Japanese individual investors through newspapers and TV, exercising caution in disseminating adverse news to Japanese institutions, and promoting and justifying CSR actions to foreign investors. It underscores the need for a strategic investor relations frameworks that considers accessibility, literacy, and investors' interests.

This study examines the relationship between sources of information for CSR activities and investors’ responses, an area under-represented in the literature. The author uses CSR announcement data, collected from newspapers to make the results more accurate and relevant.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

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.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

This study investigates how to motivate behavioral intentions toward green investment (BIGI) with the moderating effect of social media platforms usage (SMPU) among individual investors in Egypt.

The study used partial least squares structural equation modeling (PLS-SEM) to analyze the data and test hypotheses based on a sample of 550 individual investors with investment experience.

The results show that attitude, subjective norm (SN), and perceived behavioral control (PBC) have a significant relationship with investors' behavioral intention toward green investment. The moderating effect of (SMPU) supported the relationship between (SN), (PBC), and (BIGI), but (SMPU) does not support the relationship between attitude and (BIGI).

This study provides some implications for investment providers, service providers, and policymakers.

Despite the increasing global interest in climate change and its consequent opportunities and challenges for business, previous studies did not strongly emphasize green investment. So, based on the theory of planned behavior (TPB), this study sheds light on the motivational factors that may push investors' behavioral intentions toward green investment. With the increasing interest in digital transformation, the study also examined how digital platforms support (BIGI), especially in Egypt as a developing country.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

This paper aims to explore the development of investment decision tools by understanding the rationality behind the disposition effect. We suspect that not all disposition decisions are irrational. The decisions should be evaluated based on the bounded rationality of the individuals’ target and tolerance level, which is not covered in previous literature. Adding the context of individual preference (target and tolerance) in their decision could improve the classic measurement of disposition effect.

The laboratory web experiment is prepared to collect the responses in holding and selling the stocks within 14 days. Two groups of Gen Z investors are observed. The control group makes a decision based on their judgment without any system recommendation. In contrast, the second group gets help inputting their target and tolerance. Furthermore, the framing effect is also applied as a reminder of their target and tolerance to induce more holding decisions on gain but selling on loss.

The framing effect is adequate to mitigate the disposition effect but only at the early day of observation. Bounded rationality explains the rationality of liquidating the gain because the participants have reached their goal. The framing effect is not moderated by days to affect the disposition effect; over time, the disposition effect tends to be higher. A new measurement of the disposition effect in the context of bounded rationality is better than the original disposition effect coefficient.

Gen Z investors need a system aid to help their investment decisions set their target and tolerance to mitigate the disposition effect. Investment firms can make a premium feature based on real-time market data for investors to manage their assets rationally in the long run. Bounded rationality theory offers more flexibility in understanding the gap between profit maximization and irrational decisions in behavioral finance. The government can use this finding to develop a suitable policy and ecosystem to help beginner investors understand investment risk and manage their assets based on subjective risk tolerance.

The classic Proportion Gain Realized (PGR) and Proportion Loss Realized (PLR) measurements cannot accommodate several contexts of users’ targets and tolerance in their choices, which we argue need to be re-evaluated with bounded rationality. Therefore, this article proposed new measurements that account for the users’ target and tolerance level to evaluate the rationality of their decision.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

The purpose of this study is to investigate the factors affecting behaviour intention (BI) to use and actual usages of investment-related FinTech services among the zoomers (Gen Z) and millennials (Gen M) retail investors of India.

The study explores the predictive relevance of actual adoption behaviour among the two different age categories of Indian retail investors. It uses the Unified Theory of Acceptance and Use of Technology-2 and the prospect theory framework as guiding frameworks. Data has been collected from 294 retail investors, actively engaged in the investment-related FinTech services. The multi-group analysis using variance-based partial least square structured equation modelling has been used to compare the two groups. The invariance between the two groups was achieved through measurement invariance assessment.

The study reveals distinct factors significantly affecting BI to use investment-related FinTech services among Gen Z and Gen M retail investors are performance expectancy (PE) to BI, perceived risk (PR) to BI, price value (PV) to BI and PR to service trust (ST).

This study provides insights for financial providers and policymakers, emphasizing different factors influencing BI to use investment-related FinTech services in both age groups. Notably, habit emerges as a common factor influencing the actual usage of investment-related FinTech services across Gen M and Gen Z retail investors in India.

This study explores the heterogeneous behaviour of the heterogenous population in the domain of technological adoption of investment-related FinTech services in India.