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Sentiment dynamics and stock returns: the case of the German stock market

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  • Thomas Lux

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  • Thomas Lux, 2011. "Sentiment dynamics and stock returns: the case of the German stock market," Empirical Economics, Springer, vol. 41(3), pages 663-679, December.
  • Handle: RePEc:spr:empeco:v:41:y:2011:i:3:p:663-679 DOI: 10.1007/s00181-010-0397-0
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    References listed on IDEAS

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    1. Jördis Hengelbrock & Erik Theissen & Christian Westheide, 2013. "Market Response to Investor Sentiment," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(7-8), pages 901-917, September.
    2. 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.
    3. 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.
    4. 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.
    5. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, pages 394-408.
    6. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    7. 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, pages 1303-1317.
    8. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    9. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, pages 291-311.
    10. Shleifer, Andrei & Vishny, Robert W, 1997. " The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
    11. Bénédicte Vidaillet & V. D'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    12. Liu, Te-Ru & Gerlow, Mary E. & Irwin, Scott H., 1994. "The performance of alternative VAR models in forecasting exchange rates," International Journal of Forecasting, Elsevier, vol. 10(3), pages 419-433, November.
    13. Schmeling, Maik, 2007. "Institutional and individual sentiment: Smart money and noise trader risk?," International Journal of Forecasting, Elsevier, pages 127-145.
    14. Penm, J. H. W. & Terrell, R. D., 1984. "Multivariate subset autoregressive modelling with zero constraints for detecting 'overall causality'," Journal of Econometrics, Elsevier, vol. 24(3), pages 311-330, March.
    15. 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.
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    Citations

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    Cited by:

    1. Zhang, Wei & Li, Xiao & Shen, Dehua & Teglio, Andrea, 2016. "Daily happiness and stock returns: Some international evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 201-209.
    2. Dergiades, Theologos, 2012. "Do investors’ sentiment dynamics affect stock returns? Evidence from the US economy," Economics Letters, Elsevier, vol. 116(3), pages 404-407.
    3. Thomas Lux, 2013. "Inference for systems of stochastic differential equations from discretely sampled data: a numerical maximum likelihood approach," Annals of Finance, Springer, vol. 9(2), pages 217-248, May.
    4. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
    5. CURATOLA, Giuliano & DONADELLI, Michael & KIZYS, Renatas & RIEDEL, Max, 2016. "Investor Sentiment and Sectoral Stock Returns: Evidence from World Cup Games," Finance Research Letters, Elsevier, vol. 17(C), pages 267-274.
    6. Bormann, Sven-Kristjan, 2013. "Sentiment indices on financial markets: What do they measure?," Economics Discussion Papers 2013-58, Kiel Institute for the World Economy (IfW).
    7. repec:spr:eurasi:v:7:y:2017:i:3:d:10.1007_s40821-016-0063-3 is not listed on IDEAS
    8. Lux, Thomas, 2012. "Inference for systems of stochastic differential equations from discretely sampled data: A numerical maximum likelihood approach," Kiel Working Papers 1781, Kiel Institute for the World Economy (IfW).
    9. Kroujiline, Dimitri & Gusev, Maxim & Ushanov, Dmitry & Sharov, Sergey V. & Govorkov, Boris, 2015. "Forecasting stock market returns over multiple time horizons," MPRA Paper 66175, University Library of Munich, Germany.
    10. Gusev, Maxim & Kroujiline, Dimitri & Govorkov, Boris & Sharov, Sergey V. & Ushanov, Dmitry & Zhilyaev, Maxim, 2014. "Predictable markets? A news-driven model of the stock market," MPRA Paper 58831, University Library of Munich, Germany.
    11. 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.
    12. Lutz, Chandler, 2015. "The impact of conventional and unconventional monetary policy on investor sentiment," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 89-105.
    13. repec:eee:ecmode:v:64:y:2017:i:c:p:496-501 is not listed on IDEAS

    More about this item

    Keywords

    Investor sentiment; Opinion dynamics; Return predictability; G12; G14; C22;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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