Mind over market: Impact of investor sentiment on the Indian stock market

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Type of the article: Research Article

Abstract
Investor sentiment influences financial markets beyond fundamental factors. Understanding the extent of this influence on market returns is crucial for stakeholders to make informed decisions. The study analyzed the impact of investor sentiment on the National Stock Exchange (NSE). The investor sentiment index, constructed by extracting sentiments from Times of India business news articles, is used to create the first index, the Financial Index (FinDex), using FinBERT (Financial Bidirectional Encoder Representations from Transformers). The Composite Investor Sentiment Index (CISI), which consists of FinDex and selected sentiment proxy variables, is finally constructed using Principal Component Analysis. This study has analyzed the impact of CISI on selected market indices. Results indicated that stock market returns significantly influence investor sentiment. The broad market index explains 39.12% of the variations in CISI. In the sectoral indices, the percentage of variations explained by the sectoral market index is more than 40% for auto, realty, and pharma. Investor sentiment also influences stock market returns, but comparatively, the influence is minimal. Thus, sentiment lags behind stock returns rather than driving them. Bidirectional causal relation exists in the case of the auto, public sector bank, and realty sectors (p-value < 0.10). CISI can be used by investors to refine their asset allocation strategies, ensuring better market timing and reducing exposure to irrational market swings. It can also be used as an early warning system for systematic risk in financial markets.

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    • Table 1. List of variables
    • Table 2. ADF test results of the stock market returns of indices
    • Table 3. ADF test results of proxy investor sentiment variables
    • Table A1. Final variables selected for constructing the CISI
    • Table A2. Final composite investor sentiment index
    • Table B1. Lag selection
    • Table B2. VAR output of CISI and Nifty Auto, Nifty Bank, Nifty Energy, and Nifty FS
    • Table B3. VAR output of CISI and Nifty Private Bank, Nifty PSU Bank, Nifty Realty, and Nifty 50
    • Table B4. VAR output of CISI and Nifty Media, Nifty Metal, Nifty Pharma, Nifty FMCG, and Nifty IT
    • Table B5. Variance decomposition (VD) of Nifty Auto and Bank
    • Table B6. Variance decomposition (VD) of Nifty Energy and Financial Services
    • Table B7. Variance Decomposition (VD) results of Nifty FMCG and Nifty IT
    • Table B8. Variance decomposition (VD) results of Nifty Media and Nifty Metal
    • Table B9. Variance Decomposition (VD) results of Nifty Pharma and Nifty Private Bank
    • Table B10. Variance decomposition (VD) results of Nifty PSU Bank and Nifty Realty
    • Table B11. Variance decomposition results of Nifty 50
    • Table B12. Granger causality output of CISI and returns of sectoral indices
    • Conceptualization
      Aakruthi Amrut Alarnkar, K. G. Sankaranarayanan
    • Data curation
      Aakruthi Amrut Alarnkar
    • Formal Analysis
      Aakruthi Amrut Alarnkar
    • Investigation
      Aakruthi Amrut Alarnkar
    • Methodology
      Aakruthi Amrut Alarnkar, K. G. Sankaranarayanan
    • Validation
      Aakruthi Amrut Alarnkar
    • Visualization
      Aakruthi Amrut Alarnkar, K. G. Sankaranarayanan
    • Writing – original draft
      Aakruthi Amrut Alarnkar
    • Writing – review & editing
      Aakruthi Amrut Alarnkar, K. G. Sankaranarayanan
    • Project administration
      K. G. Sankaranarayanan
    • Supervision
      K. G. Sankaranarayanan
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Investment Management and Financial Innovations
Investment Management and Financial Innovations