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Optimism in Financial Markets: Stock Market Returns and Investor Sentiments

Author

Listed:
  • Chiara Limongi Concetto

    (Free University of Bolzano‐Bozen, Faculty of Economics, Italy and Sparkasse – Cassa di Risparmio, Italy)

  • Francesco Ravazzolo

    (Free University of Bolzano‐Bozen, Faculty of Economics, Italy and Centre for Applied Macro and commodity Prices, BI Norwegian Business School, Norway)

Abstract

This paper investigates how investor sentiment affects stock market returns and evaluates the predictability power of sentiment indices on U.S. and EU stock market returns. As regards the American example, evidence shows that investor sentiment indices have a negative influence on stock market returns. Concerning the European market instead, investigation provides weak results. Moreover, comparing the two markets, where investor sentiment of U.S. market tries to predict the European stock market returns, and vice versa, the analyses indicate a spillover effect from the U.S. to Europe.

Suggested Citation

  • Chiara Limongi Concetto & Francesco Ravazzolo, 2019. "Optimism in Financial Markets: Stock Market Returns and Investor Sentiments," BEMPS - Bozen Economics & Management Paper Series BEMPS56, Faculty of Economics and Management at the Free University of Bozen.
  • Handle: RePEc:bzn:wpaper:bemps56
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    References listed on IDEAS

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    1. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. Rahul Verma & Hasan Baklaci & Gokce Soydemir, 2008. "The impact of rational and irrational sentiments of individual and institutional investors on DJIA and S&P500 index returns," Applied Financial Economics, Taylor & Francis Journals, vol. 18(16), pages 1303-1317.
    5. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2014. "Forecasting stock returns under economic constraints," Journal of Financial Economics, Elsevier, vol. 114(3), pages 517-553.
    6. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    7. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    8. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    9. repec:hrv:faseco:30747159 is not listed on IDEAS
    10. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    11. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    13. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    14. 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.
    15. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2003. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, edition 1, volume 1, number 1.
    16. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
    17. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    18. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2003. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, edition 1, volume 1, number 2.
    19. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    20. Kandel, Shmuel & Stambaugh, Robert F, 1996. "On the Predictability of Stock Returns: An Asset-Allocation Perspective," Journal of Finance, American Finance Association, vol. 51(2), pages 385-424, June.
    21. Michael Lemmon & Evgenia Portniaguina, 2006. "Consumer Confidence and Asset Prices: Some Empirical Evidence," Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1499-1529.
    22. Verma, Rahul & Soydemir, Gökçe, 2009. "The impact of individual and institutional investor sentiment on the market price of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1129-1145, August.
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    Cited by:

    1. A. Fronzetti Colladon & S. Grassi & F. Ravazzolo & F. Violante, 2020. "Forecasting financial markets with semantic network analysis in the COVID-19 crisis," Papers 2009.04975, arXiv.org, revised Nov 2020.
    2. Mauro Bernardi & Stefano Grassi & Francesco Ravazzolo, 2020. "Bayesian Econometrics," JRFM, MDPI, vol. 13(11), pages 1-2, October.
    3. Rakovská, Zuzana, 2021. "Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 473-495.
    4. Tihana Škrinjarić & Branka Marasović & Boško Šego, 2021. "Does the Croatian Stock Market Have Seasonal Affective Disorder?," JRFM, MDPI, vol. 14(2), pages 1-16, February.
    5. Oguzhan Cepni & Rangan Gupta & Qiang Ji, 2021. "Sentiment Regimes and Reaction of Stock Markets to Conventional and Unconventional Monetary Policies: Evidence from OECD Countries," Working Papers 202126, University of Pretoria, Department of Economics.
    6. Pedro M. Nogueira Reis, 2022. "Determinants of Qualified Investor Sentiment during the COVID-19 Pandemic in North America, Asia, and Europe," Economies, MDPI, vol. 10(6), pages 1-20, June.
    7. Zuzana Gric & Josef Bajzik & Ondrej Badura, 2021. "Does Sentiment Affect Stock Returns? A Meta-analysis Across Survey-based Measures," Working Papers 2021/10, Czech National Bank.

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    More about this item

    Keywords

    Dynamic Bayesian econometrics; Portfolio choice; Sentiments; Stock Market Predictability;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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