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Productivity-Based Asset Pricing: Theory and Evidence

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  • Ronald J. Balvers

    (Division of Economics and Finance, West Virginia University)

  • Dayong Huang

    (Division of Economics and Finance, West Virginia University)

Abstract

This paper considers asset pricing from the production side. It differs from earlier approaches to production-based asset pricing in that the pricing kernel is derived by replacing the marginal rate of intertemporal substitution with an amended version of the marginal rate of intertemporal transformation in a complete markets economy. Relying on a general version of the traditional Real Business Cycle macro model we find that the variables determining the mean returns of all financial assets are the productivity shock as the sole factor together with the capital stock and lagged Solow residual (productivity level) as conditioning variables. Standard GMM estimation finds that our model improves on the complementary consumption-based and market-based approaches and is competitive with the Fama-French three-factor model. The model explains the size premium from differences in the unconditional sensitivity to productivity shocks—small firms are more sensitive to productivity shocks—and explains the value premium from differences in the conditional sensitivity to productivity shocks—growth stocks are more sensitive to productivity shocks in good states when the risk premium is low.

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Bibliographic Info

Paper provided by Department of Economics, West Virginia University in its series Working Papers with number 05-05 Classification- JEL: G12; E44.

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Length: 45 pages
Date of creation: 2005
Date of revision:
Handle: RePEc:wvu:wpaper:05-05

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Keywords: Cross-Sectional Asset Pricing; Productivity; Macro Factors; Production-Based Asset Pricing;

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Citations

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Cited by:
  1. Belo, Frederico, 2010. "Production-based measures of risk for asset pricing," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 146-163, March.
  2. Ronald J. Balvers & Dayong Huang, 2005. "Evaluation Of Linear Asset Pricing Models By Implied Portfolio Performance," Working Papers 05-06 Classification- JEL, Department of Economics, West Virginia University.
  3. Huang, Dayong & Wang, Fang, 2009. "Cash, investments and asset returns," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2301-2311, December.
  4. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2012. "The Adverse Impact of Gradual Temperature Change on Capital Investment," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124676, Agricultural and Applied Economics Association.
  5. Sanglim Lee, 2012. "Expected Currency Excess Returns and International Business Cycles," Working papers 2012-16, University of Connecticut, Department of Economics.
  6. Yi-Cheng Shih & Sheng-Syan Chen & Cheng-Few Lee & Po-Jung Chen, 2014. "The evolution of capital asset pricing models," Review of Quantitative Finance and Accounting, Springer, vol. 42(3), pages 415-448, April.
  7. Ron Balvers & Ding Du & Xiaobing Zhao, 2009. "What Do Financial Markets Reveal about Global Warming?," Working Papers 09-04, Department of Economics, West Virginia University.
  8. Javier Gomez Biscarri & Germán López Espinosa, . "The influence of differences in accounting standards on empirical pricing models: An application to the Fama-French model," Faculty Working Papers 13/07, School of Economics and Business Administration, University of Navarra.
  9. Kizys, Renatas & Pierdzioch, Christian, 2011. "The changing sensitivity of realized portfolio betas to U.S. output growth: An analysis based on real-time data," Journal of Economics and Business, Elsevier, vol. 63(3), pages 168-186, May.
  10. Szymon Grabowski, 2007. "Real economic activity and state of financial markets," Working Papers 7, Department of Applied Econometrics, Warsaw School of Economics.
  11. Hsu, Po-Hsuan & Huang, Dayong, 2010. "Technology prospects and the cross-section of stock returns," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 39-53, January.

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