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.

Investor sentiment antecedents

2019 ◽  
Vol 11 (1) ◽  
pp. 36-54 ◽  
Author(s):  
Ranjan Dasgupta ◽  
Rashmi Singh
Keyword(s):  
Decision Making ◽  
Stock Market ◽  
Emerging Market ◽  
Investment Decision ◽  
Investor Sentiment ◽  
Equation Modeling ◽  
Content Type ◽  
Investment Decision Making ◽  
Retail Investors ◽  
Specific Factors

PurposeThe 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.Design/methodology/approachFirst, 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.FindingsThe 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.Practical implicationsThe 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.Originality/valueThe 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.

Impact of investor sentiment on decision-making in Indian stock market: an empirical analysis

2019 ◽  
Vol 17 (1) ◽  
pp. 66-83 ◽  
Author(s):  
Haritha P.H. ◽  
Rashmi Uchil
Keyword(s):  
Decision Making ◽  
Social Interaction ◽  
Investment Decision ◽  
Investor Sentiment ◽  
Individual Investors ◽  
Content Type ◽  
Market Effect ◽  
Factors Influencing ◽  
The Individual ◽  
The Relationship

Purpose The purpose of this paper is to analyze the relationship between the factors influencing investors sentiment and investment decision-making (DM) of the individual investors. This paper proposes a unique conceptual framework that incorporates the herding, market and awareness factors that are leading to investor sentiment (IS) and decision-making process of the individual investors. Design/methodology/approach This study has conducted a questionnaire-based survey to collect data from 875 individual investors through the convenience sampling method. Structural equation modeling was used to evaluate the relationship between factors, namely, market effect, herd behavior, media, social interaction and advocate recommendation that influences IS and DM. Findings The present study found that market effect and herding are the most significantly influencing factors of investors sentiment. Among the sources of awareness, the internet has the lowest influence when compared to media, social interaction and advocate recommendation. Practical implications This study will help individual investors to avoid the problems faced while making an investment decision. The study could help investors to select a suitable investment aid and avoid repeating expensive errors, which arise due to investors’ sentiment. It is recommended to increase the awareness regarding investors’ sentiment among individuals, so as to increase their understanding about the financial settings and to make them confident while investing. The present study also sheds light upon the behavior of Indian individual investors so that policymakers can take appropriate measures to provide the proper guidance. Policymakers can conduct awareness campaigns to increase investors’ knowledge on the market condition and to enhance proper investment DM among them. Originality/value To best of the authors’ knowledge, previous studies have focused on limited factors at a time. The present study has investigated how factors influencing investors sentiment, namely, market factors (MF), herding as well as awareness would influence investment DM among individual investors in India. The influence of these factors has never been studied simultaneously in the context of Indian individual investors’ DM.

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.

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.

The influence of big data analytics management capabilities on supply chain preparedness, alertness and agility

2019 ◽  
Vol 32 (2) ◽  
pp. 297-318 ◽  
Author(s):  
Santanu Mandal
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Investment Decision ◽  
Big Data Analytics ◽  
Content Type ◽  
Investment Decision Making ◽  
Management Capabilities ◽  
The Impact

Purpose The importance of big data analytics (BDA) on the development of supply chain (SC) resilience is not clearly understood. To address this, the purpose of this paper is to explore the impact of BDA management capabilities, namely, BDA planning, BDA investment decision making, BDA coordination and BDA control on SC resilience dimensions, namely, SC preparedness, SC alertness and SC agility. Design/methodology/approach The study relied on perceptual measures to test the proposed associations. Using extant measures, the scales for all the constructs were contextualized based on expert feedback. Using online survey, 249 complete responses were collected and were analyzed using partial least squares in SmartPLS 2.0.M3. The study targeted professionals with sufficient experience in analytics in different industry sectors for survey participation. Findings Results indicate BDA planning, BDA coordination and BDA control are critical enablers of SC preparedness, SC alertness and SC agility. BDA investment decision making did not have any prominent influence on any of the SC resilience dimensions. Originality/value The study is important as it addresses the contribution of BDA capabilities on the development of SC resilience, an important gap in the extant literature.

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.

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.

Behavioural biases in investment decision making – a systematic literature review

2015 ◽  
Vol 7 (1) ◽  
pp. 88-108 ◽  
Author(s):  
Satish Kumar ◽  
Nisha Goyal
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Empirical Research ◽  
Systematic Literature Review ◽  
Investment Decision ◽  
Future Research ◽  
Behavioural Finance ◽  
Content Type ◽  
Investment Decision Making ◽  
The Impact

Purpose – The purpose of this paper is to systematically review the literature published in past 33 years on behavioural biases in investment decision-making. The paper highlights the major gaps in the existing studies on behavioural biases. It also aims to raise specific questions for future research. Design/methodology/approach – We employ systematic literature review (SLR) method in the present study. The prominence of research is assessed by studying the year of publication, journal of publication, country of study, types of statistical method, citation analysis and content analysis on the literature on behavioural biases. The present study is based on 117 selected articles published in peer- review journals between 1980 and 2013. Findings – Much of the existing literature on behavioural biases indicates the limited research in emerging economies in this area, the dominance of secondary data-based empirical research, the lack of empirical research on individuals who exhibit herd behaviour, the focus on equity in home bias, and indecisive empirical findings on herding bias. Research limitations/implications – This study focuses on individuals’ behavioural biases in investment decision-making. Our aim is to analyse the impact of cognitive biases on trading behaviour, volatility, market returns and portfolio selection. Originality/value – The paper covers a considerable period of time (1980-2013). To the best of authors’ knowledge, this study is the first using systematic literature review method in the area of behavioural finance and also the first to examine a combination of four different biases involved in investment decision-making. This paper will be useful to researchers, academicians and those working in the area of behavioural finance in understanding the impact of behavioural biases on investment decision-making.

scholarly journals The The Impact of Behavioral Aspects on Investment Decision Making

2021 ◽  
Vol 10 (1) ◽  
pp. 15-27
Author(s):  
Ninditya Nareswari ◽  
Alifia Salsabila Balqista ◽  
Nugroho Priyo Negoro
Keyword(s):  
Decision Making ◽  
Structural Equation ◽  
Investment Decision ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Herd Behavior ◽  
Investment Decision Making ◽  
Behavioral Aspects ◽  
The Impact

This study aims to investigate the impact of behavioral aspects (sentiment investor, overconfidence, salience, overreaction, and herd behavior) on investment decision making. The sample contained 413 individual investors—used partial least square structural equation modeling (PLS-SEM) as a data analysis technique. The results showed that sentiment investors, overconfidence, salience, overreaction, and herd behavior positively affect investment decision making. The finding of this study has important implications for the investor to understand themselves to anticipate bias in investment decision making.

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