An overview of investor sentiment: Identifying themes, trends, and future direction through bibliometric analysis
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Received May 13, 2022;Accepted August 12, 2022;Published September 7, 2022
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Author(s)Link to ORCID Index: https://orcid.org/0000-0002-1657-6456Link to ORCID Index: https://orcid.org/0000-0002-9848-9718Link to ORCID Index: https://orcid.org/0000-0001-7847-1791
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DOIhttp://dx.doi.org/10.21511/imfi.19(3).2022.19
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Article InfoVolume 19 2022, Issue #3, pp. 229-242
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Investor sentiment is the result of trading behavior and irrational beliefs of investors leading to high volatility and market mispricing. This review aims to study the entire spectrum of articles in the domain of investor sentiment using a bibliometric analysis approach. To this end, the study analyzes a total of 1,919 articles published in the Scopus database between 1979 and 2022. The review uncovers major themes, leading authors, influencing articles, trend topics, top contributing countries, and affiliations. The review shows that the research in the domain of investor sentiment is growing exponentially with an annual growth rate of 15.88%, and the year 2020 witnessed the highest number of scientific productions accounting for 252 (13.68%) total publications. The results display that the USA and China are leading countries in terms of the total contribution and volume of studies from respective authors. The review also reveals that existing research in the field has mainly focused on themes such as market efficiency, asset pricing, stock returns, sentiment analysis, IPO underpricing, overreaction, and volatility, whereas Covid-19 and Bitcoin depicted as emerging themes from recent scholarly works.
- Keywords
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JEL Classification (Paper profile tab)G40, G41, G12
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References50
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Tables6
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Figures8
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- Figure 1. Bibliometrix and recommended science mapping workflow
- Figure 2. Inclusion-exclusion criteria
- Figure 3. Annual scientific production
- Figure 4. Three-field plot of author’s country, authors, and keywords
- Figure 5. Top 20 most cited countries
- Figure 6. Word cloud analysis showing most frequently used keywords
- Figure 7. Thematic map
- Figure 8. Alluvial diagram of thematic evolution
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- Table 1. Characteristics of the bibliometric study
- Table 2. Data synthesis indicating primary information and summary of the sources
- Table 3. Annual scientific production
- Table 4. Top 20 most relevant authors, author’s impact, and author’s affiliation
- Table 5. Top 20 the most influencing articles
- Table 6. Top 20 most frequently used author keywords associated with investor sentiment
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Conceptualization
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
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Data curation
Aditi N. Kamath
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Formal Analysis
Aditi N. Kamath
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Investigation
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
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Methodology
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
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Resources
Aditi N. Kamath
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Software
Aditi N. Kamath
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Validation
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
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Writing – original draft
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
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Writing – review & editing
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
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Project administration
Sandeep S. Shenoy, Subrahmanya Kumar N.
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Supervision
Sandeep S. Shenoy, Subrahmanya Kumar N.
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Visualization
Sandeep S. Shenoy, Subrahmanya Kumar N.
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Conceptualization
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Influence of news on rational decision making by financial market investors
Investment Management and Financial Innovations Volume 16, 2019 Issue #3 pp. 142-156 Views: 2401 Downloads: 426 TO CITE АНОТАЦІЯThe impact of news on individual investor decision is explicit as investors need to update, adapt and forecast returns with constraints of time, uncertainty and resources to be successful. The aim is to understand and review the influence of news on individual investor’s decision making in stock markets and identify the impact of different type of news on individual investor’s decision making in stock markets, assess the behavioral reaction and investment decisions made by investors before and after there is news item, identify the linking effect on behavioral theories and biases, develop a generalized decision making conceptual model to understand the impact of news on investor’s reaction, decision and its linkages along with the behavioral bias. Theoretical basis/methodology for processing of news by investors is assumed to be based on Broadbent’s filter theory (1958) and due to cognitive informational inefficiency of investors it assesses the attention and the investor’s reaction of overreaction and underreaction, which do not comply with efficient market hypothesis theory. The reasons for its noncompliance are found by relating it with behavioral theories. The results explain how investor screens with filters and give attention to news only when it affects their portfolio or investment objective and strategies. It is concluded that investor’s decision making depends on degree of information penetration, information content, information influence, specific internal factors and generic external and on investors prevailing at that given circumstances. This gives us the solution to comprehend the investor’s reaction, decision and unresolved reversals, short- and long-term overreaction.
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Understanding the preference of individual retail investors on green bond in India: An empirical study
Dhaval Prajapati , Dipen Paul , Sushant Malik , Dharmesh K. Mishra doi: http://dx.doi.org/10.21511/imfi.18(1).2021.15Investment Management and Financial Innovations Volume 18, 2021 Issue #1 pp. 177-189 Views: 2315 Downloads: 987 TO CITE АНОТАЦІЯThe biggest challenge facing countries, including India, is creating and managing an LCR (low carbon resilient) economy, which balances the need for high growth rates and is environmentally sustainable. The green bond market provides investors the means to help change the economy into an LCR economy. The study was undertaken to understand the key drivers and the factors influencing the individual retail investor’s decision to invest in green bonds. A survey instrument was designed and administered through the snowball sampling technique to 125 Indian respondents of various age groups who were eligible to invest in the Indian bond market. SPSS software was used to conduct a descriptive analysis followed by regression and conjoint analyses. The study results suggest that the Environmental, Social, and Governance (ESG) rating and credit rating of the green bond issuers are the key factors that influence an individual’s investment decision. The findings also highlight that incentives such as tax exemptions and awareness of green bonds also affect an investor’s decision. This research stands out as one of the first attempts to understand the Indian retail investors’ perception of a green bond.
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Applied prospect theory: assessing the βs of M&A-intensive firms
Investment Management and Financial Innovations Volume 16, 2019 Issue #2 pp. 236-248 Views: 1469 Downloads: 145 TO CITE АНОТАЦІЯBehavioral components of Kahneman and Tversky’s (1979) prospect theory (PT) were applied to derive an adjusted Capital Asset Pricing Model (CAPM) in the estimation of merger and acquisition-intensive firms’ expected returns. The premise was that the CAPM – rooted in expected utility theory – is violated by the behavioral biases identified in prospect theory. Kahneman and Tversky’s prospect theory (1979) has demonstrated that weaknesses abound in the viability of classical utility theory predictions. For mergers and acquisitions, firms appear to be isolated from and immune to human error, yet decisions which involve the undertaking of capital-intensive projects are delegated to senior management. These individuals are prone to cognitive biases and personalized risk appetites that may (and often do) compromize attitudes and behavior when it comes to pricing risky ventures. Having established that beta estimates using linear regression are inferior, the CAPM was implemented utilizing beta estimates obtained from the Kalman filter. The results obtained were assessed for their long-term market price predictive accuracy. The authors test the reliability of the CAPM as a predictor of price, observe the rationality of human behavior in capital markets, and attempt to model premiums to adjust CAPM returns to a level that more appropriately accounts for firm specific risk. The researchers show that market participants behave irrationally when assessing M&A firms’ specific risk. Logistic regression coupled with the development of a risk premium was implemented to correct the original Kalman filter returns and was tested for improvements in predictive power.