Idiosyncratic volatility, investor sentiment, and returns of the GCC stock markets

  • Received September 11, 2021;
    Accepted November 15, 2021;
    Published November 22, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.18(4).2021.17
  • Article Info
    Volume 18 2021, Issue #4, pp. 190-202
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This work is licensed under a Creative Commons Attribution 4.0 International License

Standard finance theory suggests that idiosyncratic volatility should not influence stock returns. In reality, if investors are unable to achieve efficient diversification, such risk may affect stock returns. The purpose of the study is to examine the presence of idiosyncratic volatility and sentiment in the stock markets of the GCC (Gulf Cooperation Council) countries.
Monthly idiosyncratic volatility is estimated using the Fama-French three-factor model. A unified sentiment proxy for each market is created by employing Principal Component Analysis (PCA). Then, Ordinary Least Squares (OLS) regressions are applied. F-statistics, t-statistics, and adjusted R2s are used to test the presence of idiosyncratic volatility and sentiment in the GCC markets.
Findings show that the effect of sentiment on stock returns is observed across all the GCC markets. Investor sentiment can weakly explain the effect of idiosyncratic volatility on stock returns. In general, investors do not price expected idiosyncratic volatility, and only the unexpected part of it affects stock returns.
Overall, the first implication for investors is that they must consider market sentiment to predict the cross-section of stock prices and should not completely ignore the influence of idiosyncratic volatility on stocks. Secondly, the implication for policymakers is that they should motivate companies to go public so that investors have more options to diversify their portfolios across different sectors.

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    • Table 1. Impact of idiosyncratic volatility and sentiment on individual market returns
    • Table 2. Impact of idiosyncratic volatility on size-portfolio returns
    • Table 3. Impact of expected and unexpected idiosyncratic volatility on size-portfolio returns
    • Table 4. Impact of idiosyncratic volatility and sentiment on size-portfolio returns
    • Table 5. Impact of expected and unexpected idiosyncratic volatility and sentiment on size-portfolio returns
    • Conceptualization
      Shah Saeed Hassan Chowdhury
    • Data curation
      Shah Saeed Hassan Chowdhury
    • Formal Analysis
      Shah Saeed Hassan Chowdhury
    • Funding acquisition
      Shah Saeed Hassan Chowdhury
    • Investigation
      Shah Saeed Hassan Chowdhury
    • Methodology
      Shah Saeed Hassan Chowdhury
    • Project administration
      Shah Saeed Hassan Chowdhury
    • Resources
      Shah Saeed Hassan Chowdhury
    • Software
      Shah Saeed Hassan Chowdhury
    • Supervision
      Shah Saeed Hassan Chowdhury
    • Validation
      Shah Saeed Hassan Chowdhury
    • Visualization
      Shah Saeed Hassan Chowdhury
    • Writing – original draft
      Shah Saeed Hassan Chowdhury
    • Writing – review & editing
      Shah Saeed Hassan Chowdhury