Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market
In the last two decades, the subject of investor sentiment has attracted the attention of researchers across the globe. This study attempts to examine the bi-directional relationship between investor sentiment and stock market returns in the Indian market by focusing on both contemporaneous and lagg...
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| Format: | Article |
| Language: | English |
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LLC "CPC "Business Perspectives"
2022-10-01
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| Series: | Investment Management & Financial Innovations |
| Subjects: | |
| Online Access: | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/17228/IMFI_2022_04_Yadav.pdf |
| _version_ | 1826952759590518784 |
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| author | Ajit Yadav Anindita Chakraborty Vijaya |
| author_facet | Ajit Yadav Anindita Chakraborty Vijaya |
| author_sort | Ajit Yadav |
| collection | DOAJ |
| description | In the last two decades, the subject of investor sentiment has attracted the attention of researchers across the globe. This study attempts to examine the bi-directional relationship between investor sentiment and stock market returns in the Indian market by focusing on both contemporaneous and lagged relationships between investor sentiment and market returns. It also attempts to study the effect of lagged market returns on the current market returns. This study constructs an investor sentiment index for the Indian market using the principal component analysis technique. The results of the regression analysis between the investor sentiment index and stock market returns establish that current sentiment positively affects current market returns, and one-month lagged sentiment negatively affects current market returns. Further, it is found that a one-month lagged market return has a positive association with the current market returns. Moreover, using the VAR model, this study found the existence of a contemporaneous and lagged bidirectional relationship between investor sentiment and market returns. The results of impulse response analysis and variance decomposition analysis also support the presence of a sentiment-return bidirectional relationship but show that the effect of sentiment on market returns is more pronounced than the effect of market returns on investor sentiment. |
| first_indexed | 2024-04-12T01:32:02Z |
| format | Article |
| id | doaj.art-9fa595f29bfa4539894825dba60c06b6 |
| institution | Directory Open Access Journal |
| issn | 1810-4967 1812-9358 |
| language | English |
| last_indexed | 2025-02-17T23:11:53Z |
| publishDate | 2022-10-01 |
| publisher | LLC "CPC "Business Perspectives" |
| record_format | Article |
| series | Investment Management & Financial Innovations |
| spelling | doaj.art-9fa595f29bfa4539894825dba60c06b62024-12-02T07:05:23ZengLLC "CPC "Business Perspectives"Investment Management & Financial Innovations1810-49671812-93582022-10-01194839810.21511/imfi.19(4).2022.0717228Modeling a bi-directional sentiment-return relationship: Evidence from the Indian marketAjit Yadav0https://orcid.org/0000-0001-5529-9941Anindita Chakraborty1https://orcid.org/0000-0001-9251-0937Vijaya2https://orcid.org/0000-0003-1623-0620MBA, Doctoral Student, Institute of Management Studies, Banaras Hindu UniversityPh.D., Lecturer, Institute of Management Studies, Banaras Hindu UniversityMBA, Doctoral Student, Institute of Management Studies, Banaras Hindu UniversityIn the last two decades, the subject of investor sentiment has attracted the attention of researchers across the globe. This study attempts to examine the bi-directional relationship between investor sentiment and stock market returns in the Indian market by focusing on both contemporaneous and lagged relationships between investor sentiment and market returns. It also attempts to study the effect of lagged market returns on the current market returns. This study constructs an investor sentiment index for the Indian market using the principal component analysis technique. The results of the regression analysis between the investor sentiment index and stock market returns establish that current sentiment positively affects current market returns, and one-month lagged sentiment negatively affects current market returns. Further, it is found that a one-month lagged market return has a positive association with the current market returns. Moreover, using the VAR model, this study found the existence of a contemporaneous and lagged bidirectional relationship between investor sentiment and market returns. The results of impulse response analysis and variance decomposition analysis also support the presence of a sentiment-return bidirectional relationship but show that the effect of sentiment on market returns is more pronounced than the effect of market returns on investor sentiment.https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/17228/IMFI_2022_04_Yadav.pdfGeweke testGranger causalityimpulse response analysisprincipal component analysisvariance decomposition analysisvector autoregression |
| spellingShingle | Ajit Yadav Anindita Chakraborty Vijaya Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market Investment Management & Financial Innovations Geweke test Granger causality impulse response analysis principal component analysis variance decomposition analysis vector autoregression |
| title | Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market |
| title_full | Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market |
| title_fullStr | Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market |
| title_full_unstemmed | Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market |
| title_short | Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market |
| title_sort | modeling a bi directional sentiment return relationship evidence from the indian market |
| topic | Geweke test Granger causality impulse response analysis principal component analysis variance decomposition analysis vector autoregression |
| url | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/17228/IMFI_2022_04_Yadav.pdf |
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