Modeling a bi-directional sentiment-return relationship: Evidence from the Indian market

  • 280 Views
  • 53 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

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.

view full abstract hide full abstract
    • Figure 1. Sentiment index
    • Figure 2. Trend of market returns and investor sentiment
    • Figure 3. VAR-Impulse response analysis
    • Table 1. Correlation coefficient between PROVSENT and contemporaneous and lag value of sentiment proxies
    • Table 2. Results of unit root test, augmented Dickey-Fuller test, and Phillips-Perron test
    • Table 3. Regression analysis results
    • Table 4. Lag length selection using various lag selection criteria
    • Table 5. Granger-causality test
    • Table 6. Variance decomposition analysis
    • Table B1. The sentiment proxies for measuring investor sentiment
    • Table C1. Descriptive statistics of the sentiment proxies
    • Conceptualization
      Ajit Yadav, Vijaya
    • Data curation
      Ajit Yadav
    • Formal Analysis
      Ajit Yadav, Vijaya
    • Investigation
      Ajit Yadav
    • Methodology
      Ajit Yadav, Vijaya
    • Project administration
      Ajit Yadav, Anindita Chakraborty
    • Writing – original draft
      Ajit Yadav
    • Software
      Anindita Chakraborty
    • Supervision
      Anindita Chakraborty
    • Validation
      Vijaya
    • Visualization
      Vijaya