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Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model

Expanding the panel model of Pesaran (2006) and Bai (2009), we propose a dynamic panel specification with Bayesian approach to capture the impact of unobservable industry-wide shocks to stock price movements. We employ fundamental accounting information to control company specific shocks and equity market index to capture market wide common shocks. Our model is designed to resolve the potential multicollinearity problem that is known to exist when the industry factors are considered by extracting the industry-wide shocks using Bayesian method.

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Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 347.

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Length: 28 pages
Date of creation: 01 Mar 2014
Date of revision:
Handle: RePEc:uts:rpaper:347
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  1. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
  2. John Geweke & Guofu Zhou, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," CEMA Working Papers 276, China Economics and Management Academy, Central University of Finance and Economics.
  3. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.
  4. Elisa Tosetti & Francesco Moscone, 2007. "Health Expenditure and Income in the United States," Discussion Papers in Economics 07/14, Department of Economics, University of Leicester.
  5. Seung C. Ahn & Young H. Lee & Peter Schmidt, 2006. "Panel Data Models with Multiple Time-Varying Individual Effects," Working Papers 0702, University of Crete, Department of Economics.
  6. Borja Larrain & Motohiro Yogo, 2005. "Does firm value move too much to be justified by subsequent changes in cash flow?," Working Papers 05-18, Federal Reserve Bank of Boston.
  7. Joshua C.C. Chan & Roberto Leon-Gonzalez & Rodney W. Strachan, 2013. "Invariant Inference and Efficient Computation in the Static Factor Model," CAMA Working Papers 2013-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  8. Clement, Michael B. & Hales, Jeffrey & Xue, Yanfeng, 2011. "Understanding analysts' use of stock returns and other analysts' revisions when forecasting earnings," Journal of Accounting and Economics, Elsevier, vol. 51(3), pages 279-299, April.
  9. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, 07.
  10. Chen, Peter & Zhang, Guochang, 2007. "How do accounting variables explain stock price movements? Theory and evidence," Journal of Accounting and Economics, Elsevier, vol. 43(2-3), pages 219-244, July.
  11. JULES H. van BINSBERGEN & RALPH S. J. KOIJEN, 2010. "Predictive Regressions: A Present-Value Approach," Journal of Finance, American Finance Association, vol. 65(4), pages 1439-1471, 08.
  12. Lessard, Donald R, 1974. "World, National, and Industry Factors in Equity Returns," Journal of Finance, American Finance Association, vol. 29(2), pages 379-91, May.
  13. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
  14. Harford, Jarrad, 2005. "What drives merger waves?," Journal of Financial Economics, Elsevier, vol. 77(3), pages 529-560, September.
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