An overview of investor sentiment: Identifying themes, trends, and future direction through bibliometric analysis
-
Received May 13, 2022;Accepted August 12, 2022;Published September 7, 2022
-
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
-
DOIhttp://dx.doi.org/10.21511/imfi.19(3).2022.19
-
Article InfoVolume 19 2022, Issue #3, pp. 229-242
- TO CITE АНОТАЦІЯ
-
Cited by9 articlesJournal title:Article title:DOI:Volume: / Issue: / First page: / Year:Contributors:Journal title: Investment Management and Financial InnovationsArticle title: ESG vs conventional indices: Comparing efficiency in the Ukrainian stock marketDOI: 10.21511/imfi.20(2).2023.01Volume: 20 / Issue: 2 / First page: 1 / Year: 2023Contributors: Alex Plastun, Inna Makarenko, Liudmyla Huliaieva, Tetiana Guzenko, Iryna ShalyhinaJournal title: South Asian Journal of Business and Management CasesArticle title: Mapping the Conceptual and Intellectual Structure of the Investor’s Financial Behaviour: A Bibliometric AnalysisDOI: 10.1177/22779779241264350Volume: 13 / Issue: 2 / First page: 228 / Year: 2024Contributors: Zeenat Jamal Ansari, Seema Gupta, Meena BhatiaJournal title: Investment Management and Financial InnovationsArticle title: Institutional investors’ role in implementing book building: Views of market participantsDOI: 10.21511/imfi.21(4).2024.09Volume: 21 / Issue: 4 / First page: 104 / Year: 2024Contributors: Jas Bahadur Gurung, Lija Boro, Ramkrishna ChapagainJournal title: Cogent Economics & FinanceArticle title: Does investor sentiment affect the Indian stock market? Evidence from Nifty 500 and other selected sectoral indicesDOI: 10.1080/23322039.2024.2303896Volume: 12 / Issue: 1 / First page: / Year: 2024Contributors: Aditi N. Kamath, Sandeep S. Shenoy, Abhilash Abhilash, Subrahmanya Kumar NJournal title: International Review of Financial AnalysisArticle title: Demystifying the dynamic relationship between news sentiment index and ESG stocks: Evidence from time-frequency wavelet analysisDOI: 10.1016/j.irfa.2024.103698Volume: 96 / Issue: / First page: 103698 / Year: 2024Contributors: Imran Yousaf, Azza Bejaoui, Shoaib Ali, Yanshuang LiJournal title: Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežìArticle title: Intelligent system for clustering users of social networks based on the message sentiment analysisDOI: 10.23939/sisn2023.13.121Volume: 13 / Issue: / First page: 121 / Year: 2023Contributors: Taras Batiuk, Dmytro DosynJournal title: Investment Management and Financial InnovationsArticle title: Impact of personality traits on investment decision-making: Mediating role of investor sentiment in IndiaDOI: 10.21511/imfi.20(3).2023.17Volume: 20 / Issue: 3 / First page: 200 / Year: 2023Contributors: Aditi N. Kamath, Sandeep S. Shenoy, Abhilash, Subrahmanya Kumar N.Journal title: Journal of Financial StudiesArticle title: ANALYZING FINANCIAL MARKETS EFFICIENCY: INSIGHTS FROM A BIBLIOMETRIC AND CONTENT REVIEWDOI: 10.55654/JFS.2024.9.16.09Volume: 9 / Issue: 16 / First page: / Year: 2024Contributors: Paul Handro, Bogdan Dima
- 911 Views
-
376 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
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
-
JEL Classification (Paper profile tab)G40, G41, G12
-
References50
-
Tables6
-
Figures8
-
- 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
-
- 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
-
- Aggarwal, D. (2022). Defining and measuring market sentiments a review of the literature. Qualitative Research in Financial Markets, 14(2), 270-288.
- Aramonte, S., & Avalos, F. (2021). The raising influence of retail investors. BIS Quarterly Review.
- Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.
- Baker, M. P., & Wurgler, J. A. (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance, 61(4), 1645-1680.
- Baker, M. P., & Wurgler, J. A. (2007). Investor Sentiment in the Stock Market. SSRN Electronic Journal, 21(2).
- Barber, B. M. (1994). Noise trading and prime and score premiums. Journal of Empirical Finance, 1(3-4), 251-278.
- Barberis, N., Shleifer, A., & Vishnya, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307-343.
- Bathia, D., & Bredin, D. (2018). Investor sentiment: Does it augment the performance of asset pricing models? International Review of Financial Analysis, 59, 290-303.
- Bergman, Nittai. K., & Roychowdhury, S. (2008). Investor Sentiment and Corporate Disclosure. Journal of Accounting Research, 46(5).
- Bessler, W., & Thies, S. (2007). The long-run performance of initial public offerings in Germany. Managerial Finance, 33(6), 420-441.
- Bouteska, A. (2020). Some evidence from a principal component approach to measure a new investor sentiment index in the Tunisian stock market. Managerial Finance, 46(3), 401-420.
- Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27.
- Brown, G. W., & Cliff, M. T. (2005). Investor Sentiment and Asset Valuation. The Journal of Business, 78(2), 405-440.
- Chordia, T., Kurov, A., Muravyev, D., & Subrahmanyam, A. (2020). Index Option Trading Activity and Market Returns. Management Science.
- Chu, X., Wu, C., & Qiu, J. (2015). A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach. Applied Economics, 48(21), 1915-1924.
- Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146-166.
- Das, S. R., & Chen, M. Y. (2007). Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web. Management Science, 53(9), 1375-1388.
- De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Positive Feedback Investment Strategies and Destabilizing Rational Speculation. The Journal of Finance, 45(2), 379-395.
- Debata, B., & Mahakud, J. (2018). Economic policy uncertainty and stock market liquidity: dose financial crisis make any difference. Journal of Financial Economic Policy, 10(1), 112-135.
- Dergiades, T. (2012). Do investors’ sentiment dynamics affect stock returns? Evidence from the US economy. Economics Letters, 116(3), 404-407.
- Dhall, R., & Singh, B. (2020). The COVID-19 Pandemic and Herding Behaviour: Evidence from India’s Stock Market. Millennial Asia, 097639962096463.
- Eachempati, P., Srivastava, P. R., & Panigrahi, P. K. (2021). Sentiment Analysis of COVID-19 Pandemic on the Stock Market. American Business Review, 24(1), 141-165.
- Entrop, O., Frijns, B., & Seruset, M. (2020). The determinants of price discovery on Bitcoin markets. Journal of Futures Markets, 40(5), 816-837.
- Finter, P., Niessen-Ruenzi, A., & Ruenzi, S. (2010). The Impact of Investor Sentiment on the German Stock Market. SSRN Electronic Journal.
- Guégan, D., & Renault, T. (2020). Does investor sentiment on social media provide robust information for Bitcoin returns predictability? Finance Research Letters, 101494.
- Gurdgiev, C., & O’Loughlin, D. (2020). Herding and anchoring in cryptocurrency markets: Investor reaction to fear and uncertainty. Journal of Behavioral and Experimental Finance, 25, 100271.
- Huang, D., Jiang, F., Tu, J., & Zhou, G. (2014). Investor Sentiment Aligned: A Powerful Predictor of Stock Returns. Review of Financial Studies, 28(3), 791-837.
- Janková, Z., & Dostál, P. (2019). Utilization of Artificial Intelligence for Sensitivity Analysis in the Stock Market. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 67(5), 1269-1283.
- John Maynard Keynes. (1936). The general theory of employment, Interest and Money. London: Macmillan and Co.
- Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263.
- Kathpal, S., Akhtar, A., Zaheer, A., & Khan, M. N. (2021). Covid-19 and heuristic biases: evidence from India. Journal of Financial Services Marketing, 26(4), 305-316.
- Kling, G., & Gao, L. (2008). Chinese institutional investors’ sentiment. Journal of International Financial Markets, Institutions and Money, 18(4), 374-387.
- Kumar, A., & Lee, C. M. C. (2006). Retail Investor Sentiment and Return Comovements. The Journal of Finance, 61(5), 2451-2486.
- Lee, C. M. C., Shleifer, A., & Thaler, R. H. (1991). Investor Sentiment and the Closed-End Fund Puzzle. The Journal of Finance, 46(1), 75-109.
- Lemmon, M., & Portniaguina, E. (2006). Consumer Confidence and Asset Prices: Some Empirical Evidence. Review of Financial Studies, 19(4), 1499-1529.
- Liu, S. (2015). Investor Sentiment and Stock Market Liquidity. Journal of Behavioral Finance, 16(1), 51-67.
- López-Cabarcos, M. Á., Pérez-Pico, A. M., Piñeiro-Chousa, J., & Šević, A. (2021). Bitcoin volatility, stock market and investor sentiment. Are they connected? Finance Research Letters, 38, 101399.
- Malkiel, B. G. (2003). The Efficient Market Hypothesis and Its Critics. Journal of Economic Perspectives, 17(1), 59-82.
- Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & Delgado López-Cózar, E. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics, 12(4), 1160-1177.
- Mongeon, P., & Paul-Hus, A. (2015). The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics, 106(1), 213-228.
- Neal, R., & Wheatley, S. M. (1998). Do Measures of Investor Sentiment Predict Returns? The Journal of Financial and Quantitative Analysis, 33(4), 523.
- Olsen, R. A. (1998). Behavioral Finance and Its Implications for Stock-Price Volatility. Investment Management and Research Financial Analysis Journal, 54(2), 10-18.
- Osipovich, A. (2020). Individual-Investor Boom reshapes U.S. Stock Market. Wall Street Journal.
- Paule-Vianez, J., Gómez-Martínez, R., & Prado-Román, C. (2020). A bibliometric analysis of behavioural finance with mapping analysis tools. European Research on Management and Business Economics.
- Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of Empirical Finance, 16(3), 394-408.
- Singh, B. (2021). A Bibliometric Analysis of Behavioral Finance and Behavioral Accounting. American Business Review, 24(2), 198-230.
- Stambaugh, R. F., Yu, J., & Yuan, Y. (2012). The short of it: Investor sentiment and anomalies. Journal of Financial Economics, 104(2), 288-302.
- Tetlock, P. C. (2007). Giving Content to Investor Sentiment: The Role of Media in the Stock Market. The Journal of Finance, 62(3), 1139-1168.
- Zhang, J., Yu, Q., Zheng, F., Long, C., Lu, Z., & Duan, Z. (2015). Comparing keywords plus of WOS and author keywords: A case study of patient adherence research. Journal of the Association for Information Science and Technology, 67(4), 967-972.
- Zhu, J., & Liu, W. (2020). A tale of two databases: the use of Web of Science and Scopus in academic papers. Scientometrics, 123(1), 321-335.
-
-
Conceptualization
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Data curation
Aditi N. Kamath
-
Formal Analysis
Aditi N. Kamath
-
Investigation
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Methodology
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Resources
Aditi N. Kamath
-
Software
Aditi N. Kamath
-
Validation
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Writing – original draft
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Writing – review & editing
Aditi N. Kamath, Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Project administration
Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Supervision
Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Visualization
Sandeep S. Shenoy, Subrahmanya Kumar N.
-
Conceptualization
-
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: 2424 Downloads: 430 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.
-
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: 2365 Downloads: 1002 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.
-
The effect of investor sentiment on the means of earnings management
Investment Management and Financial Innovations Volume 15, 2018 Issue #1 pp. 10-17 Views: 1473 Downloads: 507 TO CITE АНОТАЦІЯPrior research has shown that a firm’s tendency to meet or beat earning targets is greater during bad economic times than good times. The paper extends this line of research by investigating which means of earnings management is used in different states of economy. A sample of non-financial companies listed on Korea Securities Market from 2003 to 2011 is used for empirical tests. The findings of this study are summarized as follows. The magnitude of discretionary accruals is negatively related to investment sentiment, indicating that firms tend to use positive discretionary accruals to manipulate reported income upward when the sentiment is pessimistic. However, the real activity based earnings management is not significantly associated with the state of economy. Collectively, this study contributes to behavioral finance and accounting literature by suggesting that managers use discretionary portion of accruals, but do not change their real operating activities, in order to meet or beat earnings targets in economic downturn.