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

Author

Listed:
  • KiHoon Jimmy Hong
  • Bin Peng
  • Xiaohui Zhang

    (School of Management and Governance, Murdoch University)

Abstract

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.

Suggested Citation

  • KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2014. "Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model," Research Paper Series 347, Quantitative Finance Research Centre, University of Technology, Sydney.
    • Handle: RePEc:uts:rpaper:347
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    File URL: https://www.uts.edu.au/sites/default/files/rp347.pdf
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    References listed on IDEAS

    as
    1. KiHoon Jimmy Hong & Eliza Wu, 2014. "Can Momentum Factors Be Used to Enhance Accounting Information based Fundamental Analysis in Explaining Stock Price Movements?," Research Paper Series 346, Quantitative Finance Research Centre, University of Technology, Sydney.
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    Cited by:

    1. Ahmadi, Maryam & Manera, Matteo & Sadeghzadeh, Mehdi, 2016. "Global oil market and the U.S. stock returns," Energy, Elsevier, vol. 114(C), pages 1277-1287.
    2. Hong, KiHoon & Wu, Eliza, 2016. "The roles of past returns and firm fundamentals in driving US stock price movements," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 62-75.
    3. Yu, Gun Jea & Hong, KiHoon, 2016. "Patents and R&D expenditure in explaining stock price movements," Finance Research Letters, Elsevier, vol. 19(C), pages 197-203.

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    More about this item

    Keywords

    Common Factor Structural Error; Common Shocks; Stock Price Movements; Accounting Fundamentals; Bayesian Gibbs Sampler;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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