Development and validation of behavioral biases scale: a SEM approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ritika ◽  
Nawal Kishor
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Phase 1 ◽  
Secondary Data ◽  
Higher Order ◽  
Second Order ◽  
Individual Investors ◽  
Content Type ◽  
Behavioral Biases ◽  
Investment Decision Making

PurposeThis paper attempts to identify the biases in decision-making of individual investors. The paper aims to develop and validate a higher-order behavioral biases scale.Design/methodology/approachScale development is done by identifying the relevant items of the scale through existing literature and then, adding new items for some biases. In phase 1, using a structured questionnaire, data was collected from 274 investors who invest in financial markets. The major dimensions of the scale have been pruned by using exploratory factor analysis administered on data collected in phase 1. Higher-order CFA is used to analyze the data and to validate the scale on another set of data (collected in phase 2) containing 576 investors.FindingsThe study reveals that the scale for measuring behavioral biases has many dimensions. It has two second-order factors and 13 zero-order constructs. Two second-order constructs have been modeled on the basis of cause of errors in investment decision-making, that is, biases caused due to cognition, biases caused due to emotions.Originality/valueBehavioral biases are yet to receive a due attention, especially, in the Indian context. The present research is focusing on providing an empirically tested scale to test the behavioral biases. Some of the biases, which have been analyzed using secondary data in previous studies, have been tested with the help of statements in this study.

scholarly journals An Analysis of Behavioral Biases in Investment Decision-Making

2019 ◽  
Vol 10 (4) ◽  
pp. 55 ◽  
Author(s):  
Geetika Madaan ◽  
Sanjeet Singh
Keyword(s):  
Decision Making ◽  
Positive Impact ◽  
Stock Exchange ◽  
Investment Decision ◽  
Investment Decisions ◽  
Individual Investors ◽  
Behavioral Biases ◽  
Investment Decision Making ◽  
Survey Responses ◽  
The Impact

Individual investor’s behavior is extensively influenced by various biases that highlighted in the growing discipline of behavior finance. Therefore, this study is also one of another effort to assess the impact of behavioral biases in investment decision-making in National Stock Exchange. A questionnaire is designed and through survey responses collected from 243 investors. The present research has applied inferential statistics and descriptive statistics. In the existing study, four behavioral biases have been reviewed namely, overconfidence, anchoring, disposition effect and herding behavior. The results show that overconfidence and herding bias have significant positive impact on investment decision. Overall results conclude that individual investors have limited knowledge and more prone towards making psychological errors. The findings of the study also indicate the existence of these four behavioral biases on individual investment decisions. This study will be helpful to financial intermediaries to advice their clients. Further, study can be elaborated to study other behavioral biases on investment decisions.

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

2019 ◽  
Vol 12 (3) ◽  
pp. 297-314 ◽  
Author(s):  
Jinesh Jain ◽  
Nidhi Walia ◽  
Sanjay Gupta
Keyword(s):  
Decision Making ◽  
Behavioral Finance ◽  
Investment Decision ◽  
Investment Decisions ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Behavioral Biases ◽  
Investment Decision Making ◽  
Overconfidence Bias ◽  
Hierarchy Process

Purpose 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. Design/methodology/approach 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. Findings 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).” Research limitations/implications 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. Practical implications 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. Originality/value 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.

scholarly journals How do emotional intelligence and behavioral biases of investors determine their investment decisions?

2020 ◽  
Vol 14 (1) ◽  
pp. 35-47
Author(s):  
Saloni Raheja ◽  
Babli Dhiman
Keyword(s):  
Decision Making ◽  
Stock Exchange ◽  
Investment Decision ◽  
Sample Selection ◽  
Investment Decisions ◽  
Risk Tolerance ◽  
Content Type ◽  
Behavioral Biases ◽  
Investment Decision Making ◽  
The Impact

Purpose In earlier studies, research has shown that EI is the only element, which influences the ways in which people develop in their lives, jobs and social skills control their emotions and get along with other people. It is EI that dictates the way people deal with one another and understand emotions. The research gap is to explore the impact of behavioral factors and investors psychology on their investment decision-making. Design/methodology/approach The information was gathered from 500 financial specialists. The region of research was the financial specialists who contribute through LSC Securities Ltd. in Punjab State. The purposive testing system was used in this examination. Findings The investigation found that the positive connection between the conduct predispositions of the financial specialists and venture choices of the speculators and positive connection between enthusiastic insight of the financial specialists and their venture choices. Yet, the authors found that the enthusiastic insight better foresees the venture choices of the financial specialists than the conduct predispositions of the speculators. Among the different elements of conduct inclinations of the speculator’s lament and carelessness are identified with the financial specialist’s venture choices. Among the various estimations of eager understanding – care, dealing with emotions, motivation, empathy and social aptitudes are related to the hypothesis decisions of the monetary pros. Research limitations/implications The sample selection was based on purposive sampling, rather than a random probability sample. The sample was area specific, restricted only to Ludhiana Stock Exchange in Punjab state. Therefore, the results of the study cannot be generalized with certainty to all the investors investing through other exchanges in other states. The inferences are based on the assumption that the data provided by the investors are true and correct. The findings may be relevant for other stock exchanges as that of the Ludhiana Stock Exchange. However, the authors do not claim the generalization of the results. Practical implications This study also helps to understand the relationship between investment decision-making and risk tolerance of investors. It will helpful for the financial advisors to know the behavioral biases of investors while making an investment decision, and therefore, they can advise investors properly to mitigate such biases. It may help the investors in understanding the subjective part of their behavior and control their emotions while taking decisions for their investment in stock market options. Social implications This research will help investment advisors and finance professionals to judge investors’ attitudes toward risk in a better way, which leads to better investment decisions. Originality/value This study is my own study and it is original and has not been published anywhere.

Past behaviour, financial literacy and investment decision-making process of individual investors

2020 ◽  
Vol 15 (6) ◽  
pp. 1243-1263 ◽  
Author(s):  
Rajdeep Kumar Raut
Keyword(s):  
Decision Making ◽  
Financial Literacy ◽  
Structural Equation ◽  
Investment Decision ◽  
Individual Investors ◽  
Successful Implementation ◽  
Snowball Sampling ◽  
Content Type ◽  
Investment Decision Making ◽  
External Variables

PurposeThis study aims to explore the importance of past behaviour and financial literacy in the investment decision-making of individual investors and examines the validity of the theory of planned behaviour in this context.Design/methodology/approachThe study used a self-administered questionnaire and adopted the convenience sampling technique followed by a snowball sampling method for the survey to collect data from the individual investors covering the four distinct states of India. Collected data were analysed on AMOS 20.0 using two-step structural equation modelling (SEM).FindingsResults indicated a significant effect of all the predictive variables. Past behaviour showed no significant direct impact on investor's intention; however, it had an indirect significant relationship while mediated by the attitude of investors. The multiple squared correlation (R2) showed that the final model could explain 36% of the variance in investors' intention towards stock investment which signified a successful implementation of the TPB model along with external variables added to it. Moreover, Indian investors were found to be highly influenced, primarily, by social pressure which could be curbed through financial literacy.Practical implicationsA significant importance of subjective norms was found on stock market participation which could be a strategic theme for the government and the policymakers to educate investors through their opinion leaders for increasing their participation. Moreover, by doing so investors could control their behaviour and take rational decisions.Originality/valueThis study extended the understandings of investor's decision-making behaviour using TPB by incorporating the two external variables viz., Financial literacy and past behaviour. The addition of past behaviour is perhaps the novelty of this article since such examination has not been conducted empirically especially in the case of developing countries like India.

Influence of investor sentiment and its antecedent on investment decision-making using partial least square technique

2020 ◽  
Vol 43 (11) ◽  
pp. 1441-1459
Author(s):  
Haritha P.H. ◽  
Rashmi Uchil
Keyword(s):  
Decision Making ◽  
Social Interaction ◽  
Stock Market ◽  
Investment Decision ◽  
Investor Sentiment ◽  
Partial Least Square ◽  
Individual Investors ◽  
Content Type ◽  
Investment Decision Making ◽  
The Impact

Purpose The purpose of this paper is to determine whether individual investor sentiment and its factors influence investment decision-making behavior in the Indian stock market. The study contributes to the novel conceptual framework that integrates the impact of investor sentiment and outlines the role of its factors (herding, media factor, advocate recommendation and social interaction) during the investment decision-making process. Design/methodology/approach In this paper, data were collected using a structured questionnaire survey from Indian individual investors. It uses self-reported sources of information collected via a survey of individual investors and estimated the linkage via path modeling. The collected data were analyzed using partial least square structural equation modeling to examine the relationship between the construct, namely, herding, media, advocate recommendation and social interaction with investor sentiment and investment decision-making. Findings The study shows that herding, media factor, advocate recommendation and social interaction significantly and positively influence the investor sentiment. Among all the factors, social interaction has the lowest influence on investor sentiment. The study also reveals that investor sentiment has a positive impact on investment decision-making. Practical implications The study provides valuable insights for the individual investors, financial advisors, policymakers and other stakeholders. Knowledge of behavioral finance would enhance the decision-making capabilities of individual investors in the stock market. Thus, the study calls for the need to increase awareness among Indian investors about behavioral finance and its usefulness in investment decision-making. The paper also sheds light upon the influence of investor sentiment and its antecedents on investment decision-making. The study confirms that the investor relies on their sentiment while making investment decisions. Hence, the stakeholders in the stock market should focus on investor sentiment and other psychological aspects of individual investors as well. Originality/value There are very few studies that deal with the behavioral aspects of individual investors in an emerging market context. The study mainly focuses on the antecedent of investor sentiment and its influence on investment decision-making in the Indian stock market. To the best of authors’ knowledge, the present study unique nature that examines the impact of the antecedent of investor sentiment which was not explored in the Indian context and investment decision-making of individual investors.

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

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maqsood Ahmad ◽  
Syed Zulfiqar Ali Shah
Keyword(s):  
Decision Making ◽  
Risk Perception ◽  
Financial Literacy ◽  
Investment Decision ◽  
Investment Decisions ◽  
Individual Investors ◽  
Content Type ◽  
Investment Decision Making ◽  
And Performance

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.

Deriving wisdom from virtual investing communities: an alternative strategy to stock recommendations

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rahul Kumar ◽  
Shubhadeep Mukherjee ◽  
Bipul Kumar ◽  
Pradip Kumar Bala
Keyword(s):  
Decision Making ◽  
Stock Market ◽  
Business Processes ◽  
Investment Decision ◽  
Investment Strategy ◽  
Individual Investors ◽  
Content Type ◽  
Stock Market Development ◽  
Economic Wealth ◽  
Investment Decision Making

Purpose Colossal information is available in cyberspace from a variety of sources such as blogs, reviews, posts and feedback. The mentioned sources have helped in improving various business processes from product development to stock market development. This paper aims to transform this wealth of information in the online medium to economic wealth. Earlier approaches to investment decision-making are dominated by the analyst's recommendations. However, their credibility has been questioned for herding behavior, conflict of interest and favoring underwriter's firms. This study assumes that members of the online crowd who have been reliable, profitable and knowledgeable in the recent past will continue to be so soon. Design/methodology/approach The authors identify credible members as experts using multi-criteria decision-making tools. In this work, an alternative actionable investment strategy is proposed and demonstrated through a mock-up. The experimental prototype is divided into two phases: expert selection and investment. Findings The created portfolio is comparable and even profitable than several major global stock indices. Practical implications This work aims to benefit individual investors, investment managers and market onlookers. Originality/value This paper takes into account factors: the accuracy and trustworthiness of the sources of stock market recommendations. Earlier work in the area has focused solely intelligence of the analyst for the stock recommendation. To the best of the authors’ knowledge, this is the first time that the combined intelligence of the virtual investment communities has been considered to make stock market recommendations.

Factors influencing investor’s decision making in Pakistan

2018 ◽  
Vol 10 (1) ◽  
pp. 70-87 ◽  
Author(s):  
Muhammad Haroon Rasheed ◽  
Amir Rafique ◽  
Tayyaba Zahid ◽  
Muhammad Waqar Akhtar
Keyword(s):  
Decision Making ◽  
Locus Of Control ◽  
Structural Equation ◽  
Quantitative Research ◽  
Investment Decision ◽  
Equation Modeling ◽  
Individual Investors ◽  
Content Type ◽  
Investment Decision Making ◽  
The Impact

Purpose The purpose of this paper is to look at the impact of two most commonly used heuristics, namely, representative bias and availability bias on investment decision making and to check that either locus of control interact with the said relations through theoretical proposal and then verification through empirical evidence. Design/methodology/approach The study is a quantitative research using a survey questionnaire for its data collection. Data are collected from 227 investors operating at Islamabad, Lahore, and Sargodha in Pakistan and analyzed using structural equation modeling while the interaction effect is analyzed through simple linear regression following the rules set by Baron and Kenny (1986). Findings The results reveal that both of the heuristics under study significantly cause investors to deviate from rational decision making while the locus of control have no significant moderating effect. Originality/value The proposed model provides insight on how the behavioral factors can lead investors to suboptimal decision making. This study is first of its kind to quantify the degree of irrationality caused by these factors. The findings of this study are practically useful for individual investors, investment managers, and also for policy makers.

Digital innovation in wealth management landscape: the moderating role of robo advisors in behavioural biases and investment decision-making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankita Bhatia ◽  
Arti Chandani ◽  
Rajiv Divekar ◽  
Mita Mehta ◽  
Neeraja Vijay
Keyword(s):  
Decision Making ◽  
Loss Aversion ◽  
Investment Decision ◽  
Equation Modeling ◽  
Individual Investors ◽  
Digital Innovation ◽  
Content Type ◽  
Advisory Services ◽  
Wealth Management ◽  
Investment Decision Making

Purpose Innovation is the way of life and we see various innovative techniques and methods being introduced in our daily life. This study aims to focus on digital innovation in the wealth management domain. This study examines the effect of usage of robo-advisory services in investment decision-making and behavioural biases, i.e. overconfidence and loss aversion. Such studies are more pronounced in developed countries and little has been studied about investor behaviour in association with advisory services in developing countries such as India. Design/methodology/approach Overconfidence and loss-aversion biases, investment decision-making and advisory services questions are measured using a five-point Likert scale. The number of respondents was 172 investors. A purposive sampling is used for gathering responses from investors. Structural equation modeling model was run using AMOS 22 version software package. Findings The authors found that behavioural biases positively and significantly influence the irrationalities of investment decision-making. The findings of this study also provide empirical evidence that the usage of robo-advisory services, by individual investors, is still incapable of mitigating behavioural biases, such as overconfidence bias and loss-aversion bias. Research limitations/implications The sample size of this study could be a limiting factor. This study is limited only to two biases, while other behavioural biases affect the investment decision-making of the investors, which can be considered for future research along with the impact of robo-advisory services in different socio-cultural backgrounds. Practical implications This study will assist fintech start-ups, banks, architecture of robo advisors, product owners and wealth management service providers improvise their products, platforms and offerings of these automated advisory services. This could help individual investors to mitigate their behavioural biases in investment decision-making. Social implications This study is useful to society as the awareness of robo-advisory services is very less, at present, and there is a need to increase the usage of these services to extend the benefit of this to the lower stratum of society. These services would be useful to all investors who find it difficult to afford financial advisors and help them mitigate their behavioural biases for investment decision-making. Originality/value This study is the first of its type that establishes the linkage between behavioural biases, digital innovation in fintech, i.e. robo-advisory services and individual investor’s investment decision-making in individual investor of the Indian stock market.

Do investors exhibit behavioral biases in investment decision making? A systematic review

2018 ◽  
Vol 10 (2) ◽  
pp. 210-251 ◽  
Author(s):  
Syed Aliya Zahera ◽  
Rohit Bansal
Keyword(s):  
Decision Making ◽  
Behavioral Finance ◽  
Institutional Investors ◽  
Investment Decision ◽  
Research Work ◽  
Investment Decisions ◽  
Financial Advisors ◽  
Content Type ◽  
Behavioral Biases ◽  
Investment Decision Making

Purpose The purpose of this paper is to study and describe several biases in investment decision-making through the review of research articles in the area of behavioral finance. It also includes some of the analytical and foundational work and how this has progressed over the years to make behavioral finance an established and specific area of study. The study includes behavioral patterns of individual investors, institutional investors and financial advisors. Design/methodology/approach The research papers are analyzed on the basis of searching the keywords related to behavioral finance on various published journals, conference proceedings, working papers and some other published books. These papers are collected over a period of year’s right from the time when the most introductory paper was published (1979) that contributed this area a basic foundation till the most recent papers (2016). These articles are segregated into biases wise, year-wise, country-wise and author wise. All research tools that have been used by authors related to primary and secondary data have also been included into our table. Findings A new era of understanding of human emotions, behavior and sentiments has been started which was earlier dominated by the study of financial markets. Moreover, this area is not only attracting the, attention of academicians but also of the various corporates, financial intermediaries and entrepreneurs thus adding to its importance. The study is more inclined toward the study of individual and institutional investors and financial advisors’ investors but the behavior of intermediaries through which some of them invest should be focused upon, narrowing down population into various variables, targeting the expanding economies to reap some unexplained theories. This study has identified 17 different types of biases and also summarized in the form of tables. Research limitations/implications The study is based on some of the most recent findings to have a quick overview of the latest work carried out in this area. So far very few extensive review papers have been published to highlight the research work in the area of behavioral finance. This study will be helpful for new researches in this field and to identify the areas where possible work can be done. Practical implications Practical implication of the research is that companies, policymakers and issuers of securities can watch out of investors’ interest before issuing securities into the market. Social implications Under the Social Implication, investors can recognize several behavioral biases, take sound investment decisions and can also minimize their risk. Originality/value The essence of this paper is the identification of 17 types of biases and the literature related to them. The study is based on both, the literature on investment decisions and the biases in investment decision-making. Such study is less prevalent in the developing country like India. This paper does not only focus on the basic principles of behavioral finance but also explain some emerging concepts and theories of behavioral finance. Thus, the paper generates interest in the readers to find the solutions to minimize the effect of biases in decision-making.

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