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Revisiting the investor sentiment–stock returns relationship: A multi-scale perspective using wavelets

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  • Lao, Jiashun
  • Nie, He
  • Jiang, Yonghong

Abstract

This paper employs SBW proposed by Baker and Wurgler (2006) to investigate the nonlinear asymmetric Granger causality between investor sentiment and stock returns for US economy while considering different time-scales. The wavelet method is utilized to decompose time series of investor sentiment and stock returns at different time-scales to focus on the local analysis of different time horizons of investors. The linear and nonlinear asymmetric Granger methods are employed to examine the Granger causal relationship on similar time-scales. We find evidence of strong bilateral linear and nonlinear asymmetric Granger causality between longer-term investor sentiment and stock returns. Furthermore, we observe the positive nonlinear causal relationship from stock returns to investor sentiment and the negative nonlinear causal relationship from investor sentiment to stock returns.

Suggested Citation

  • Lao, Jiashun & Nie, He & Jiang, Yonghong, 2018. "Revisiting the investor sentiment–stock returns relationship: A multi-scale perspective using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 420-427.
  • Handle: RePEc:eee:phsmap:v:499:y:2018:i:c:p:420-427
    DOI: 10.1016/j.physa.2018.02.043
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    1. Kumari, Jyoti & Mahakud, Jitendra, 2015. "Does investor sentiment predict the asset volatility? Evidence from emerging stock market India," Journal of Behavioral and Experimental Finance, Elsevier, vol. 8(C), pages 25-39.
    2. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    3. Dergiades, Theologos, 2012. "Do investors’ sentiment dynamics affect stock returns? Evidence from the US economy," Economics Letters, Elsevier, vol. 116(3), pages 404-407.
    4. Kling, Gerhard & Gao, Lei, 2008. "Chinese institutional investors' sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 374-387, October.
    5. 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.
    6. 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.
    7. Aloui, Chaker & Hkiri, Besma & Lau, Chi Keung Marco & Yarovaya, Larisa, 2016. "Investors’ sentiment and US Islamic and conventional indexes nexus: A time–frequency analysis," Finance Research Letters, Elsevier, vol. 19(C), pages 54-59.
    8. Ko, Jun-Hyung & Lee, Chang-Min, 2015. "International economic policy uncertainty and stock prices: Wavelet approach," Economics Letters, Elsevier, vol. 134(C), pages 118-122.
    9. Rua, António & Nunes, Luís C., 2009. "International comovement of stock market returns: A wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 632-639, September.
    10. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    11. Xiaojun Chu & Chongfeng Wu & Jianying Qiu, 2016. "A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach," Applied Economics, Taylor & Francis Journals, vol. 48(21), pages 1915-1924, May.
    12. Kyrtsou, Catherine & Labys, Walter C., 2006. "Evidence for chaotic dependence between US inflation and commodity prices," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 256-266, March.
    13. Yonghong Jiang & Bin Mo & He Nie, 2018. "Does investor sentiment dynamically impact stock returns from different investor horizons? Evidence from the US stock market using a multi-scale method," Applied Economics Letters, Taylor & Francis Journals, vol. 25(7), pages 472-476, April.
    14. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    15. Alzahrani, Mohammed & Masih, Mansur & Al-Titi, Omar, 2014. "Linear and non-linear Granger causality between oil spot and futures prices: A wavelet based test," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 175-201.
    16. Gençay, Ramazan & Signori, Daniele, 2015. "Multi-scale tests for serial correlation," Journal of Econometrics, Elsevier, vol. 184(1), pages 62-80.
    17. Stelios Bekiros & Rangan Gupta & Clement Kyei, 2016. "A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices," Applied Economics, Taylor & Francis Journals, vol. 48(31), pages 2895-2898, July.
    18. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    19. Zhang, Yongjie & Zhang, Yuzhao & Shen, Dehua & Zhang, Wei, 2017. "Investor sentiment and stock returns: Evidence from provincial TV audience rating in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 288-294.
    20. Saafi Sami & Farhat Abdeljelil & Haj Mohamed Meriem Bel, 2015. "Testing the relationships between shadow economy and unemployment: empirical evidence from linear and nonlinear tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 585-608, December.
    21. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    22. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    23. François Benhmad, 2012. "Modeling Nonlinear Granger Causality between the Oil price and U.S Dollar," Post-Print hal-03062497, HAL.
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