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Firms’ fundamentals, macroeconomic variables and quarterly stock prices in the US

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  • Bhargava, Alok

Abstract

This paper modeled the effects of firms’ fundamentals such as total assets and long-term debt and of macroeconomic variables such as unemployment and interest rates on quarterly stock prices of over 3000 US firms in the period 2000–07. The merged CRSP/Compustat database was augmented by macroeconomic variables and comprehensive dynamic models were estimated by maximum likelihood taking into account heterogeneity across firms. Likelihood ratio statistics were developed for sequentially testing hypotheses regarding the adequacy of macroeconomic variables in the models. The main findings were that the estimated coefficients of lagged stock prices in simple dynamic random effects models were in the interval 0.90–0.95. Second, comprehensive dynamic models for stock prices showed that the firms’ earnings per share, total assets, long-term debt, dividends per share, and unemployment and interest rates were significant predictors; there were significant interactions between firms’ long-term debt and interest rates. Finally, implications of the results for corporate policies are discussed.

Suggested Citation

  • Bhargava, Alok, 2014. "Firms’ fundamentals, macroeconomic variables and quarterly stock prices in the US," Journal of Econometrics, Elsevier, vol. 183(2), pages 241-250.
    • Handle: RePEc:eee:econom:v:183:y:2014:i:2:p:241-250
    DOI: 10.1016/j.jeconom.2014.05.014
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    References listed on IDEAS

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    1. Alok Bhargava & J. D. Sargan, 2006. "Estimating Dynamic Random Effects Models From Panel Data Covering Short Time Periods," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 1, pages 3-27, World Scientific Publishing Co. Pte. Ltd..
    2. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    3. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    4. A. Bhargava & L. Franzini & W. Narendranathan, 2006. "Serial Correlation and the Fixed Effects Model," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 4, pages 61-77, World Scientific Publishing Co. Pte. Ltd..
    5. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    6. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    7. Alok Bhargava, 2006. "Identification and Panel Data Models with Endogenous Regressors," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 3, pages 49-60, World Scientific Publishing Co. Pte. Ltd..
    8. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    9. Alok Bhargava, 2010. "An econometric analysis of dividends and share repurchases by US firms," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(3), pages 631-656, July.
    10. Sargan, J D, 1980. "Some Tests of Dynamic Specification for a Single Equation," Econometrica, Econometric Society, vol. 48(4), pages 879-897, May.
    11. Arrow, Kenneth J, 1982. "Risk Perception in Psychology and Economics," Economic Inquiry, Western Economic Association International, vol. 20(1), pages 1-9, January.
    12. Alok Bhargava, 2006. "Wald Tests And Systems Of Stochastic Equations," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 2, pages 29-48, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. James Nguyen & Wei-Xuan Li & Clara Chia-Sheng Chen, 2022. "Mean Reversions in Major Developed Stock Markets: Recent Evidence from Unit Root, Spectral and Abnormal Return Studies," JRFM, MDPI, vol. 15(4), pages 1-20, April.
    2. Pooja Joshi & A K Giri, 2015. "Dynamic Relations between Macroeconomic Variables and Indian Stock Price: An Application of ARDL Bounds Testing Approach," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 5(10), pages 1119-1133, October.
    3. Mingyang Li & Linlin Niu & Andrew Pua, 2020. "Market Pricing of Fundamentals at the Shanghai Stock Exchange: Evidence from a Dividend Discount Model with Adaptive Expectations," Working Papers 2020-12-30, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    4. Syed Jawad Hussain Shahzad & Dene Hurley & Román Ferrer, 2021. "U.S. stock prices and macroeconomic fundamentals: Fresh evidence using the quantile ARDL approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3569-3587, July.
    5. GIRI A. K. & JOSHI Pooja, 2017. "The Impact Of Macroeconomic Indicators On Indian Stock Prices: An Empirical Analysis," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 12(1), pages 61-78, April.
    6. Mahdi Moradi & Andrea Appolloni & Grzegorz Zimon & Hossein Tarighi & Maede Kamali, 2021. "Macroeconomic Factors and Stock Price Crash Risk: Do Managers Withhold Bad News in the Crisis-Ridden Iran Market?," Sustainability, MDPI, vol. 13(7), pages 1-16, March.

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    More about this item

    Keywords

    Compustat and CRSP databases; Dynamic random effects models; Endogeneity; Maximum likelihood; Macroeconomic variables; Value investing;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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