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Forecasting TAIEX and FITX with Affirmative and Doubtful Investor Sentiments

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  • Tzu-Pu Chang
  • Yu-Wei Chan
  • Ping-Huang Wang

Abstract

The existing literature have used media messages as a proxy variable for investor sentiment, but they mainly classify sentiment into positive or negative categories based on the words used in news articles, without much attention to the degree of affirmative or doubtful conveyed by the words used. Thus, in addition to classifying news content into positive or negative sentiment, this study also measures the degree of affirmative or doubtful expressed in the news articles in order to achieve more accurate predictive results. The study converts qualitative text to two quantitative scores (sentiment ratio and affirmative ratio) and investigates the predictive ability of these two variables on stock index returns and volatility in Taiwan’s case. The empirical findings indicate that only affirmative ratio exhibits a significant and negative impact on the one-day ahead returns of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the Taiwan Stock Exchange Index Futures (FITX). Additionally, the volatility of returns in both future and spot markets is significantly influenced by both sentiment ratio and affirmative ratio.

Suggested Citation

  • Tzu-Pu Chang & Yu-Wei Chan & Ping-Huang Wang, 2023. "Forecasting TAIEX and FITX with Affirmative and Doubtful Investor Sentiments," Bulletin of Applied Economics, Risk Market Journals, vol. 10(2), pages 127-140.
  • Handle: RePEc:rmk:rmkbae:v:10:y:2023:i:2:p:127-140
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    References listed on IDEAS

    as
    1. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    2. Malcolm Baker & Jeffrey Wurgler, 2000. "The Equity Share in New Issues and Aggregate Stock Returns," Journal of Finance, American Finance Association, vol. 55(5), pages 2219-2257, October.
    3. Liu, Pu & Smith, Stanley D. & Syed, Azmat A., 1990. "Stock Price Reactions to The Wall Street Journal's Securities Recommendations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(3), pages 399-410, September.
    4. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
    5. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    6. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    7. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    8. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    9. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Investor sentiment; Text-mining; TAIEX; FITX; Affirmative ratio.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G40 - Financial Economics - - Behavioral Finance - - - General

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