Investor Psychology and Security Market Under- and Overreactions

International Momentum Strategies

The primary objective of this study is to prioritize the main intentions behind investment in cryptocurrency, in spite of its volatile nature and no regulatory framework.,This research paper has worked on collective constructs of the unified theory of acceptance and use of technology (UTAUT), the technology acceptance model (TAM) and social support theory with an added construct of financial literacy. A fuzzy analytical framework has been applied to prioritize the intentions of investors.,The result indicates that “Social Influence (SI)” is the most influencing factor, while “Effort Expectancy (EE)” is the least influencing factor considered by investors. The subdimensions ranked in the top priority by investors are as follows: “I want to invest in cryptocurrencies because I have a good level of financial knowledge (FL1)”; “The people who are important to me will think that I should use cryptocurrencies (SI2)”; “I have the necessary resources to use cryptocurrencies (FC2).” The least importance is given to “It will be easy for me to become an expert in the use of cryptocurrencies (EE3).”,Few of the constructs of the UTAUT, the TAM and social support theory have been considered while prioritizing intentions. Different other intentions also prevail under different theories that need to be researched further.,Unlike previous studies, this research adds the archetype of social commerce, social support and utility theories to analyze and prioritize the behavioral perspective of using cryptocurrencies in digital transactions.,This paper fills the gap in the research study, along with assisting the regulators and cryptocurrency practitioners to widen their knowledge base and to recognize the prioritized intentions.

Prioritizing intentions behind investment in cryptocurrency: a fuzzy analytical framework

In earlier research, it has been discovered that contrary to the assumptions and theories of conventional finance, many irrational behaviors related to investment judgment occur in real life. In this paper, we have made an extensive review of various behavioral biases that affect investment decision making of the individual investors. Extant research indicates that individual investor makes his/her investment decision under the influence of some combination of behavioural biases, which mainly include disposition effect, mental accounting, investors’ overconfidence, representativeness, narrow framing, aversion to ambiguity, anchoring, availability bias, and regret aversion. Under the influence of some such biases or combination of the same, individual investors often make irrational investment decisions. And therefore, individual investors, in aggregate, earn poor long-run returns. These aspects have been highlighted in this paper. Potential solutions to mitigate the adverse impact of behavioral biases on decision making of individual investors have also been discussed. Finally, future research direction relevant to such an area has been indicated in this paper.

Behavioral Biases in the Decision Making of Individual Investors

PurposeThis paper aims to show how overconfidence influences the decisions and performance of individual investors trading on the Pakistan Stock Exchange (PSX), with the mediating role of risk perception and moderating role of financial literacy.Design/methodology/approachThe deductive approach was used, as the research is based on the theoretical framework of behavioural finance. A questionnaire and cross-sectional design were employed for data collection from the sample of 183 individual investors trading on the PSX. Hypotheses were tested through correlation and regression analysis. The Baron and Kenny method was used to test the mediation effect of risk perception and the moderation effect of financial literacy. The results of mediation and moderation were also authenticated through the PROCESS and structural equation modelling (SEM) technique.FindingsThe results suggest that risk perception fully mediates the relationships between the overconfidence heuristic on the one hand, and investment decisions and performance on the other. At the same time, financial literacy appears to moderate these relationships. The results suggest that overconfidence can impair the quality of investment decisions and performance, while financial literacy and risk perception can improve their quality.Practical implicationsThe paper encourages investors to base decisions on their financial capability and experience levels and to avoid relying on heuristics or their sentiments when making investments. It provides awareness and understanding of heuristic biases in investment management, which could be very useful for decision makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to heuristic biases. They can improve their performance by recognizing their biases and errors of judgment, to which we are all prone, resulting in better investment decisions and a more efficient market. The paper also highlights the importance on relying on professional knowledge, giving it greater weight than feelings and biases.Originality/valueThe current study is the first to focus on links between overconfidence, financial literacy, risk perception and individual investors' decisions and performance. This article enhanced the understanding of the role that heuristic-driven bias plays in the investment management, and more importantly, it went some way towards enhancing understanding of behavioural aspects and their influence on the investment decision-making and performance in an emerging market. It also adds to the literature in the area of behavioural finance specifically the role of heuristics in investment strategies; this field is in its initial stage, even in developed countries, while, in developing countries, little work has been done.

Overconfidence heuristic-driven bias in investment decision-making and performance: mediating effects of risk perception and moderating effects of financial literacy

Research in the area of behavioral finance has demonstrated that investors exhibit irrational behavior while making investment decisions. Investor behavior usually deviates from logic and reason, and consequently, investors exhibit various behavioral biases which impact their investment decisions. The purpose of this paper is to rank the behavioral biases influencing the investment decision making of individual equity investors from the state of Punjab, India. This research would provide valuable insight into the different behavioral biases to investors and other participants of the capital market and help them in improving investment decisions.,The research is conducted on the individual equity investors of Punjab, India. Fuzzy analytic hierarchy process was applied to rank the factors influencing the decision making of individual equity investors of Punjab. The primary factors considered for the study are overconfidence bias, representative bias, anchoring bias, availability bias, regret aversion bias, loss aversion bias, mental accounting bias and herding bias.,The three most influential criteria were herding bias, loss aversion bias and overconfidence bias. The five most influential sub-criteria were “I readily sell shares that have increased in value (C61),” “News about the company (Newspapers, TV and magazines) affects my investment decision (C84),” “I invest each element of my investment portfolio separately (C71)” and “I usually hold loosing stock for long time, expecting trend reversal (C52).”,Although sample survey conducted in the present study was based on a limited sample selected from a particular area that truly represented the total population, it is considered as the limitation of this study.,The outcome of this research provides investors with a better understanding of behavioral biases that influence their decision making. This study provides them a guideline on different behavioral biases that they should consider while making investment decisions.,The research model is based on the available literature on behavioral finance and the research results and findings would add value to the existing knowledge base.

Evaluation of behavioral biases affecting investment decision making of individual equity investors by fuzzy analytic hierarchy process

Research on behavioural biases has witnessed a momentous growth in the last two decades, supported by rising interest and publication thrust shown by academic scholars. Present study maps the academic literature on the role of behavioural biases in investment decision-making. With the help of bibliometric tools, the paper highlights the current state-of-the-art and identifies significant gaps in the existing literature on behavioural biases. Through keyword and reference searching approaches, the study retrieved 212 research papers from the Scopus database. Application of performance analysis techniques has helped in identification of influential journals, prolific authors, countries and affiliations enriching the literature on behavioural biases. Scientific mapping approaches such as bibliographic coupling and thematic mapping has provided valuable insights about the conceptual and intellectual structure of the field. Finally, the research directions proposed in this review will provide a roadmap for future research.

Mapping the field of behavioural biases: a literature review using bibliometric analysis

A fuzzy analytical hierarchy process framework for stock selection in the Indian stock market

In today's competitive environment, sustainability is talked out in every sphere of life. Sustainability is a key to stability and for that roots are being focused by incorporating sustainability in higher education. The basic purpose of this paper is to prioritize the sustainability drivers in the higher education system. This research will provide fruitful insight into the sustainability drivers in the higher education system to the education industry and policymakers.,The present research is conducted on the 400 students studying in four major universities in the state of Punjab. Fuzzy analytical hierarchy process was applied to prioritize the sustainability drivers in the higher education system. The primary factors considered for the present study include social-people (social responsibility), environmental-planet (sustainable environmental practices) and financial-profit (economic value created).,The most influential criteria were environmental-planet (sustainable environmental practices) and social-people (social responsibility). The five most influential subcriteria were “Student engagement in eco co-curricular activities (C21)”, Energy efficiency measures (C23)”, “The HEI as a job driver in the city (C11)”, “Total direct energy consumption (C31)” and “Support from the HEI for local initiatives and help in growing the sustainability of the community or region (C12)”.,Although the sample survey conducted in this study was focused on a small sample selected from the state of Punjab which genuinely represented the total population, it is still considered as a limitation for the present study.,The outcome of this research provides policymakers with a better understanding of the sustainability drivers in higher education. This will further help them toward achieving the aim of sustainability.,The present research is based on the available literature on sustainability and the results of the study would add value to the existing knowledge base.

Identifying sustainability drivers in higher education through fuzzy AHP

This study aims to recognize the current dynamics, prolific contributors and salient trends and propose future research directions in the area of alternative momentum investing.,The study uses a blend of electronic database and forward reference searching to ensure the incorporation of all the significant studies. With the help of the Scopus database, the present study retrieves 122 research papers published from 1999 to 2020.,The results reveal that alternative momentum investing is an emerging area in the field of momentum investing. However, this area has witnessed an exponential growth in last ten years. The study also finds that North American, West European and East Asian countries dominate in total research publications. Through network citation analysis, the study identifies five major clusters: industrial momentum, earnings momentum, 52-week high momentum, time-series momentum and risk-managed momentum.,The present review will serve as a guide for financial researchers who intend to work on alternative momentum approaches. The study proposes several unexplored research themes in alternative momentum investing on which future studies can focus.,The study embellishes the existing literature on momentum investing by contributing the first bibliometric review on alternative momentum approaches.

Jinesh Jain

Papers

Evaluation of behavioral biases affecting investment decision making of individual equity investors by fuzzy analytic hierarchy process

Mapping the field of behavioural biases: a literature review using bibliometric analysis

A fuzzy analytical hierarchy process framework for stock selection in the Indian stock market

Identifying sustainability drivers in higher education through fuzzy AHP

Mapping the scientific research on alternative momentum investing: a bibliometric analysis