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Firm-specific news and the predictability of Consumer stocks in Vietnam

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  • Salisu, Afees A.
  • Vo, Xuan Vinh

Abstract

In this paper, we hypothesize that firm/sector-specific news will enhance the predictability of firm returns, using consumer stocks of Vietnam. We construct a news-based predictive panel data model for firm returns that accounts for unobserved common factors in line with Chudik and Pesaran (2015), and Westerlund et al. (2017). While the firm-specific news turns out to be a significant predictor of firm returns, its forecast also outperforms the model that involves aggregate stocks news as well as the historical model. Accounting for an observed common factor will further improve the forecast performance of the proposed model.

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  • Salisu, Afees A. & Vo, Xuan Vinh, 2021. "Firm-specific news and the predictability of Consumer stocks in Vietnam," Finance Research Letters, Elsevier, vol. 41(C).
    • Handle: RePEc:eee:finlet:v:41:y:2021:i:c:s1544612320316159
    DOI: 10.1016/j.frl.2020.101801
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    1. Salisu, Afees A. & Ndako, Umar B. & Akanni, Lateef O., 2020. "New evidence for the inflation hedging potential of US stock returns," Finance Research Letters, Elsevier, vol. 37(C).
    2. Vo, Xuan Vinh, 2017. "Do foreign investors improve stock price informativeness in emerging equity markets? Evidence from Vietnam," Research in International Business and Finance, Elsevier, vol. 42(C), pages 986-991.
    3. Singhal, Shelly & Ghosh, Sajal, 2016. "Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models," Resources Policy, Elsevier, vol. 50(C), pages 276-288.
    4. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Sharma, Susan Sunila, 2019. "Does Islamic stock sensitivity to oil prices have economic significance?," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 497-512.
    5. Salisu, Afees A. & Ndako, Umar B., 2018. "Modelling stock price–exchange rate nexus in OECD countries: A new perspective," Economic Modelling, Elsevier, vol. 74(C), pages 105-123.
    6. Alexander Chudik & Kamiar Mohaddes & M. Hashem Pesaran & Mehdi Raissi, 2016. "Long-Run Effects in Large Heterogeneous Panel Data Models with Cross-Sectionally Correlated Errors," Advances in Econometrics, in: Essays in Honor of man Ullah, volume 36, pages 85-135, Emerald Group Publishing Limited.
    7. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    8. Tang, Wenbin & Zhu, Lili, 2017. "How security prices respond to a surge in investor attention: Evidence from Google Search of ADRs," Global Finance Journal, Elsevier, vol. 33(C), pages 38-50.
    9. Simon Reese & Joakim Westerlund, 2016. "Panicca: Panic on Cross‐Section Averages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 961-981, September.
    10. Jan Ditzen, 2018. "Estimating dynamic common-correlated effects in Stata," Stata Journal, StataCorp LP, vol. 18(3), pages 585-617, September.
    11. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    12. 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.
    13. Kim, Neri & Lučivjanská, Katarína & Molnár, Peter & Villa, Roviel, 2019. "Google searches and stock market activity: Evidence from Norway," Finance Research Letters, Elsevier, vol. 28(C), pages 208-220.
    14. Bouri, Elie & Awartani, Basel & Maghyereh, Aktham, 2016. "Crude oil prices and sectoral stock returns in Jordan around the Arab uprisings of 2010," Energy Economics, Elsevier, vol. 56(C), pages 205-214.
    15. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    16. Ciaran Driver & Katsushi Imai & Paul Temple & Giovanni Urga, 2004. "The effect of uncertainty on UK investment authorisation: Homogenous vs. heterogeneous estimators," Empirical Economics, Springer, vol. 29(1), pages 115-128, January.
    17. Vo, Xuan Vinh, 2015. "Foreign ownership and stock return volatility – Evidence from Vietnam," Journal of Multinational Financial Management, Elsevier, vol. 30(C), pages 101-109.
    18. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    19. Büttner, David & Hayo, Bernd, 2010. "News and correlations of CEEC-3 financial markets," Economic Modelling, Elsevier, vol. 27(5), pages 915-922, September.
    20. Markus Eberhardt, 2012. "Estimating panel time-series models with heterogeneous slopes," Stata Journal, StataCorp LP, vol. 12(1), pages 61-71, March.
    21. Bijl, Laurens & Kringhaug, Glenn & Molnár, Peter & Sandvik, Eirik, 2016. "Google searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 150-156.
    22. 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.
    23. Nguyen, Cuong & Ishaq Bhatti, M. & Henry, Darren, 2017. "Are Vietnam and Chinese stock markets out of the US contagion effect in extreme events?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 480(C), pages 10-21.
    24. 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.
    25. Degiannakis, Stavros & Filis, George & Floros, Christos, 2013. "Oil and stock returns: Evidence from European industrial sector indices in a time-varying environment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 175-191.
    26. Robertson, D & Symons, J, 1992. "Some Strange Properties of Panel Data Estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(2), pages 175-189, April-Jun.
    27. Birz, Gene & Lott Jr., John R., 2011. "The effect of macroeconomic news on stock returns: New evidence from newspaper coverage," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2791-2800, November.
    28. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    29. Adachi, Yuta & Masuda, Motoki & Takeda, Fumiko, 2017. "Google search intensity and its relationship to the returns and liquidity of Japanese startup stocks," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 243-257.
    30. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
    31. Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
    32. Heiko Jacobs & Alexander Hillert, 2016. "Alphabetic Bias, Investor Recognition, and Trading Behavior," Review of Finance, European Finance Association, vol. 20(2), pages 693-723.
    33. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    34. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    35. Joakim Westerlund & Hande Karabiyik & Paresh Narayan, 2017. "Testing for Predictability in panels with General Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 554-574, April.
    36. Pham, Nga & Oh, K.B. & Pech, Richard, 2015. "Mergers and acquisitions: CEO duality, operating performance and stock returns in Vietnam," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 298-316.
    37. Degiannakis, Stavros & Filis, George & Floros, Christos, 2013. "Oil and stock price returns: Evidence from European industrial sector indices in a time-varying environment," MPRA Paper 80495, University Library of Munich, Germany.
    38. Narayan, Paresh Kumar, 2019. "Can stale oil price news predict stock returns?," Energy Economics, Elsevier, vol. 83(C), pages 430-444.
    39. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    40. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    41. Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
    42. Salisu, Afees A. & Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "Testing the predictability of commodity prices in stock returns of G7 countries: Evidence from a new approach," Resources Policy, Elsevier, vol. 64(C).
    43. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    44. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    45. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    46. Sunil K. Mohanty & Mohan Nandha, 2011. "Oil Shocks and Equity Returns: An Empirical Analysis of the US Transportation Sector," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 101-128.
    47. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    48. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    49. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Westerlund, Joakim, 2016. "Are Islamic stock returns predictable? A global perspective," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 210-223.
    50. Vo, Xuan Vinh & Ellis, Craig, 2018. "International financial integration: Stock return linkages and volatility transmission between Vietnam and advanced countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 19-27.
    51. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    52. Deepa & Paresh K Narayan, "undated". "Are Indian Stock Returns Predictable?," Working Papers 2015_07, Deakin University, Department of Economics.
    53. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2019. "A sectoral analysis of asymmetric nexus between oil price and stock returns," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 241-259.
    54. Vo, Xuan Vinh, 2016. "Does institutional ownership increase stock return volatility? Evidence from Vietnam," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 54-61.
    55. Vo, Xuan Vinh, 2017. "Trading of foreign investors and stock returns in an emerging market - Evidence from Vietnam," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 88-93.
    56. Hongquan Zhu & Lingling Jiang, 2017. "Investor recognition and stock returns: evidence from China," China Finance Review International, Emerald Group Publishing Limited, vol. 8(2), pages 199-215, December.
    57. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    58. Ni, Zhong-Xin & Wang, Da-Zhong & Xue, Wen-Jun, 2015. "Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model," Economic Modelling, Elsevier, vol. 50(C), pages 266-274.
    59. Bodnaruk, Andriy & Ostberg, Per, 2009. "Does investor recognition predict returns?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 208-226, February.
    60. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    61. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2017. "Does Financial News Predict Stock Returns? New Evidence from Islamic and Non-Islamic Stocks," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 24-45.
    62. Badi H. Baltagi & James M. Griffin & Weiwen Xiong, 2000. "To Pool Or Not To Pool: Homogeneous Versus Hetergeneous Estimations Applied to Cigarette Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 117-126, February.
    63. Vo, Xuan Vinh & Phan, Dang Bao Anh, 2017. "Further evidence on the herd behavior in Vietnam stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 33-41.
    64. Nguyen, Cuong & Hoang, Lai & Shim, Jungwook & Truong, Phuong, 2020. "Internet search intensity, liquidity and returns in emerging markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    65. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    66. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach, 2017. "Momentum strategies for Islamic stocks," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 96-112.
    67. Zhang, Bing & Wang, Yudong, 2015. "Limited attention of individual investors and stock performance: Evidence from the ChiNext market," Economic Modelling, Elsevier, vol. 50(C), pages 94-104.
    68. Westerlund, Joakim & Narayan, Paresh, 2016. "Testing for predictability in panels of any time series dimension," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1162-1177.
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