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Shipping investor sentiment and international stock return predictability

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  • Papapostolou, Nikos C.
  • Pouliasis, Panos K.
  • Nomikos, Nikos K.
  • Kyriakou, Ioannis

Abstract

Stock return predictability by investor sentiment has been subject to constant updating, but reaching a decisive conclusion seems rather challenging as academic research relies heavily on US data. We provide fresh evidence on stock return predictability in an international setting and show that shipping investor sentiment is a common leading indicator for financial markets. We establish out-of-sample predictability and demonstrate that investor sentiment is also economically significant in providing utility gains to a mean-variance investor. Finally, we find evidence that the predictive power of sentiment works best when negative forecasts are also taken into account.

Suggested Citation

  • Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
  • Handle: RePEc:eee:transe:v:96:y:2016:i:c:p:81-94
    DOI: 10.1016/j.tre.2016.10.006
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    1. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2014. "The long of it: Odds that investor sentiment spuriously predicts anomaly returns," Journal of Financial Economics, Elsevier, vol. 114(3), pages 613-619.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    4. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    5. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    6. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    7. Robin Greenwood & Samuel G. Hanson, 2015. "Waves in Ship Prices and Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 55-109.
    8. Hanno N. Lustig & Stijn G. Van Nieuwerburgh, 2005. "Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective," Journal of Finance, American Finance Association, vol. 60(3), pages 1167-1219, June.
    9. 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.
    10. 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.
    11. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    12. Nikos C. Papapostolou & Nikos K. Nomikos & Panos K. Pouliasis & Ioannis Kyriakou, 2014. "Investor Sentiment for Real Assets: The Case of Dry Bulk Shipping Market," Review of Finance, European Finance Association, vol. 18(4), pages 1507-1539.
    13. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1413, August.
    14. 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.
    15. 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.
    16. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    17. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    18. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    19. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    20. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    21. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    22. Alizadeh, Amir H. & Muradoglu, Gulnur, 2014. "Stock market efficiency and international shipping-market information," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 445-461.
    23. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1414, August.
    24. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    25. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    26. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    27. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Cointegration Rank Testing Under Conditional Heteroskedasticity," Econometric Theory, Cambridge University Press, vol. 26(6), pages 1719-1760, December.
    28. Hjalmarsson, Erik, 2010. "Predicting Global Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(1), pages 49-80, February.
    29. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    30. Driesprong, Gerben & Jacobsen, Ben & Maat, Benjamin, 2008. "Striking oil: Another puzzle?," Journal of Financial Economics, Elsevier, vol. 89(2), pages 307-327, August.
    31. Nicholas Apergis & James E. Payne, 2013. "New Evidence on the Information and Predictive Content of the Baltic Dry Index," IJFS, MDPI, vol. 1(3), pages 1-19, July.
    32. 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.
    33. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    34. Myrto Kalouptsidi, 2014. "Time to Build and Fluctuations in Bulk Shipping," American Economic Review, American Economic Association, vol. 104(2), pages 564-608, February.
    35. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    36. Henkel, Sam James & Martin, J. Spencer & Nardari, Federico, 2011. "Time-varying short-horizon predictability," Journal of Financial Economics, Elsevier, vol. 99(3), pages 560-580, March.
    37. Wright, William F. & Bower, Gordon H., 1992. "Mood effects on subjective probability assessment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 52(2), pages 276-291, July.
    38. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    39. Lutz Kilian & Daniel P. Murphy, 2014. "The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
    40. Møller, Stig V. & Rangvid, Jesper, 2015. "End-of-the-year economic growth and time-varying expected returns," Journal of Financial Economics, Elsevier, vol. 115(1), pages 136-154.
    41. Michael Lemmon & Evgenia Portniaguina, 2006. "Consumer Confidence and Asset Prices: Some Empirical Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1499-1529.
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    Cited by:

    1. Han, Liyan & Wan, Li & Xu, Yang, 2020. "Can the Baltic Dry Index predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 32(C).
    2. Zhao, Hong-Mei & He, Hong-Di & Lu, Kai-Fa & Han, Xiao-Long & Ding, Yi & Peng, Zhong-Ren, 2022. "Measuring the impact of an exogenous factor: An exponential smoothing model of the response of shipping to COVID-19," Transport Policy, Elsevier, vol. 118(C), pages 91-100.
    3. Pouliasis, Panos K. & Papapostolou, Nikos C. & Kyriakou, Ioannis & Visvikis, Ilias D., 2018. "Shipping equity risk behavior and portfolio management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 178-200.
    4. Nektarios A. Michail & Konstantinos D. Melas, 2019. "A cointegrating stock trading strategy: application to listed tanker shipping companies," Journal of Shipping and Trade, Springer, vol. 4(1), pages 1-10, December.
    5. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    6. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    7. Chi-Wei Su & Xu-Yu Cai & Ran Tao, 2020. "Can Stock Investor Sentiment Be Contagious in China?," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    8. Manolis Kavussanos & Siri Pettersen Strandenes & Helen Thanopoulou, 2022. "Special issue: ends of eras and new beginnings: twenty-first century challenges for shipping," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 347-367, June.
    9. Rameeza Andleeb & Arshad Hassan, 2023. "Impact of Investor Sentiment on Contemporaneous and Future Equity Returns in Emerging Markets," SAGE Open, , vol. 13(3), pages 21582440231, August.
    10. Konstantinos D. Melas & Photis M. Panayides & Dimitris A. Tsouknidis, 2022. "Dynamic volatility spillovers and investor sentiment components across freight-shipping markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 368-394, June.
    11. Sakawa, Hideaki & Watanabel, Naoki, 2023. "The impact of the COVID-19 outbreak on Japanese shipping industry: An event study approach," Transport Policy, Elsevier, vol. 130(C), pages 130-140.
    12. Çiðdem Kurt Cihangir, 2018. "Küresel Risk Algýsýnýn Küresel Ticaret Üzerindeki Etkisi," Isletme ve Iktisat Calismalari Dergisi, Econjournals, vol. 6(1), pages 1-10.
    13. Zhang, X. & Chen, M.Y. & Wang, M.G. & Ge, Y.E. & Stanley, H.E., 2019. "A novel hybrid approach to Baltic Dry Index forecasting based on a combined dynamic fluctuation network and artificial intelligence method," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 499-516.
    14. Bai, Xiwen & Lam, Jasmine Siu Lee & Jakher, Astha, 2021. "Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    15. Mo, Guoli & Zhang, Weiguo & Tan, Chunzhi & Liu, Xing, 2022. "Predicting the portfolio risk of high-dimensional international stock indices with dynamic spatial dependence," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).

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    More about this item

    Keywords

    Shipping investor sentiment; Stock return predictability; Out-of-sample forecast performance;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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