Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-14T15:15:58.690Z Has data issue: false hasContentIssue false
  • English
  • Français

A BAYESIAN ANALYSIS OF WEAK IDENTIFICATION IN STOCK PRICE DECOMPOSITIONS

Published online by Cambridge University Press:  07 January 2014

Nathan S. Balke ,
Jun Ma  and
Mark E. Wohar
Nathan S. Balke
Affiliation:
Southern Methodist University and Federal Reserve Bank of Dallas
Jun Ma*
Affiliation:
University of Alabama
Mark E. Wohar
Affiliation:
University of Nebraska at Omaha
*
Address correspondence to: Jun Ma, Department of Economics, Finance and Legal Studies, Culverhouse College of Commerce and Business Administration, University of Alabama, Tuscaloosa, AL 35487-0024, USA; e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper employs the state-space model to reexamine the fundamental issue in finance of whether it is the expected returns or the expected dividends growth that is primarily responsible for stock price variations. We use Bayesian methods to show that there is a substantial uncertainty about the contributions of expected returns and expected dividends to fluctuations in the price–dividend ratio when the aggregate returns and dividends data are used. The substantial uncertainty of the contributions results from the model being weakly identified. Our finding challenges the notion long held in the existing literature that it is the expected returns that contribute most to price–dividend variations.

Keywords

Weak IdentificationBayesian AnalysisStock Price DecompositionState-Space Model
Type
Articles
Information
Macroeconomic Dynamics , Volume 19 , Special Issue 4: Empirical Analysis of Business Cycles, Financial Markets, and Inflation: Essays in Honor of Charles Nelson , June 2015 , pp. 728 - 752
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Balke, Nathan S. and Wohar, Mark E. (2002) Low frequency movements in stock prices: A state-space decomposition. Review of Economics and Statistics 84, 649–667.CrossRefGoogle Scholar
Balke, Nathan S. and Wohar, Mark E. (2006) What drives stock prices? Identifying the determinants of stock price movements. Southern Economic Journal 74, 55–78.Google Scholar
Balke, Nathan S. and Wohar, Mark E. (2009) Market fundamentals versus rational bubbles in stock prices: A Bayesian perspective. Journal of Applied Econometrics 24, 35–75.CrossRefGoogle Scholar
Bansal, Ravi and Yaron, Amir (2004) Risks for the long-run: A potential resolution of the asset pricing puzzles. Journal of Finance 59, 1481–1509.CrossRefGoogle Scholar
Binsbergen, Jules H. van and Ralph S.J. Koijen (2010) Predictive regressions: A present-value approach. Journal of Finance 65, 1439–1471.CrossRefGoogle Scholar
Callen, Jeffrey L. and Segal, Dan (2004) Do accruals drive firm-level stock returns? A variance decomposition analysis. Journal of Accounting Research 43, 377–412.CrossRefGoogle Scholar
Campbell, John Y. (1991) A variance decomposition for stock returns. Economic Journal 101, 157–179.CrossRefGoogle Scholar
Campbell, John Y. and Ammer, John (1993) What moves the stock and bond markets? A variance decomposition for long-term asset returns. Journal of Finance 48, 3–37.Google Scholar
Campbell, John Y. and Cochrane, J.H. (1999) By force of habit: A consumption-based aggregate explanation of stock market behavior. Journal of Political Economy 107, 205–251.CrossRefGoogle Scholar
Campbell, John Y. and Shiller, Robert (1988a) The dividend-price ratio and expectations of future dividends and discount factors. Review of Financial Studies 1, 195–228.CrossRefGoogle Scholar
Campbell, John Y. and Shiller, Robert (1988b) Stock prices, earnings, and expected dividends. Journal of Finance 43, 661–676.CrossRefGoogle Scholar
Carter, Christopher K. and Kohn, Robert (1994) On Gibbs sampling for state-space models. Biometrika 81, 541–553.CrossRefGoogle Scholar
Chen, Long (2009) On the reversal of return and dividend growth predictability: A tale of two periods. Journal of Financial Economics 92, 128–151.CrossRefGoogle Scholar
Chen, Long, Da, Zhi, and Zhao, Xinlei (2013) What drives stock price movements? Review of Financial Studies 26, 841–876.CrossRefGoogle Scholar
Chen, Long and Zhao, Xinlei (2009) Return decomposition. Review of Financial Studies 22, 5213–5249.CrossRefGoogle Scholar
Cochrane, John (1992) Explaining the variance of price-dividend ratios. Review of Financial Studies 5, 243–280.CrossRefGoogle Scholar
Cochrane, John (2008) The dog that did not bark: A defense of return predictability. Review of Financial Studies 21, 1533–1575.CrossRefGoogle Scholar
Cuthbertson, Keith, Haves, Simon, and Nitzsche, Dirk (1999) Explaining movements in UK stock prices. Quarterly Review of Economics and Finance 39, 1–19.CrossRefGoogle Scholar
Goyal, Amit and Welch, Ivo (2008) A comprehensive look at the empirical performance of equity premium prediction. Review of Financial Studies 21, 1455–1508.Google Scholar
Hansen, Lars P., Heaton, John C., and Li, Nan (2008) Consumption strikes back? Measuring long-run risk. Journal of Political Economy 116, 260–302.CrossRefGoogle Scholar
Kim, Chang-Jin and Nelson, Charles R. (1999) State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications. Cambridge, MA: MIT Press.Google Scholar
Larrain, Borja and Yogo, Motohiro (2008) Does firm value move too much to be justified by subsequent changes in cash flow? Journal of Financial Economics 87, 200–226.CrossRefGoogle Scholar
Ma, Jun (2013) Long-run risks and its implications for the equity premium puzzle: New evidence from a multivariate framework. Journal of Money, Credit and Banking 45, 121–145.CrossRefGoogle Scholar
Ma, Jun and Nelson, Charles R. (2012) The Superiority of the LM test in a Class of Models Where the Wald Test Performs Poorly; Including Nonlinear Regression, ARMA, GARCH, and Unobserved Components. Working paper, University of Alabama and University of Washington.Google Scholar
Ma, Jun, Nelson, Charles R., and Startz, Richard (2007) Spurious inference in the GARCH(1,1) model when it is weakly identified. Studies in Nonlinear Dynamics and Econometrics 11, 1–27.CrossRefGoogle Scholar
Ma, Jun and Wohar, Mark E. (2012) Expected Returns and Expected Dividend Growth: Time to Rethink an Established Empirical Literature. Working paper, University of Alabama and University of Nebraska at Omaha.Google Scholar
Morley, James, Nelson, Charles R., and Zivot, Eric (2003) Why are unobserved component and Beveridge-Nelson trend-cycle decompositions of GDP so different? Review of Economics and Statistics 85, 235–243.CrossRefGoogle Scholar
Nelson, Charles R. and Kim, Myung J. (1993) Predictable stock returns: The role of small sample bias. Journal of Finance 48, 641–661.CrossRefGoogle Scholar
Nelson, Charles R. and Schwert, G. William (1977) On testing the hypothesis that the real rate of interest is constant. American Economic Review 67, 478–486.Google Scholar
Nelson, Charles R. and Richard Startz (2007) The zero-information-limit condition and spurious inference in weakly identified models. Journal of Econometrics 138, 47–62.CrossRefGoogle Scholar
Shiller, Robert and Beltratti, Andrea (1992) Stock prices and bond yields. Journal of Monetary Economics 30, 25–46.CrossRefGoogle Scholar
Vuolteenaho, Tuomo (2002) What drives firm-level stock returns? Journal of Finance 43, 233–264.CrossRefGoogle Scholar