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Hypothesis Testing in Predictive Regressions

  • Yakov Amihud

    (New York University)

  • Clifford Hurvich

    (New York University)

  • Yi Wang

    (New York University)

We propose a new hypothesis testing method for multi-predictor regressions with finite samples, where the dependent variable is regressed on lagged variables that are autoregressive. It is based on the augmented regressiom method (ARM; Amihud and Hurvich (2004)), which produces reduced-bias coefficients and is easy to implement. The method's usefulness is demonstrated by simulations and by an empirical example, where stock returns are predicted by dividend yield and by bond yield spread. For single-predictor regressions, we show that the ARM outperforms bootstrapping and that the ARM performs better than Lewellen's (2003) method in many situations.

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File URL: http://econwpa.repec.org/eps/fin/papers/0412/0412022.pdf
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Paper provided by EconWPA in its series Finance with number 0412022.

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Length: 47 pages
Date of creation: 15 Dec 2004
Date of revision:
Handle: RePEc:wpa:wuwpfi:0412022
Note: Type of Document - pdf; pages: 47
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Polk, Christopher & Thompson, Samuel & Vuolteenaho, Tuomo, 2006. "Cross-sectional forecasts of the equity premium," Journal of Financial Economics, Elsevier, vol. 81(1), pages 101-141, July.
  2. Alex Maynard & Katsumi Shimotsu, 2007. "Covariance-based orthogonality tests for regressors with unknown persistence," Working Papers 1122, Queen's University, Department of Economics.
  3. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
  4. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
  5. Nelson, Charles R & Kim, Myung J, 1993. " Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-61, June.
  6. Campbell, John & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Scholarly Articles 3122601, Harvard University Department of Economics.
  7. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
  8. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
  9. Yakov Amihud & Clifford Hurvich, 2004. "Predictive Regressions: A Reduced-Bias Estimation Method," Econometrics 0412008, EconWPA.
  10. Kothari, S. P. & Shanken, Jay, 1997. "Book-to-market, dividend yield, and expected market returns: A time-series analysis," Journal of Financial Economics, Elsevier, vol. 44(2), pages 169-203, May.
  11. Robert F. Stambaugh, 1999. "Predictive Regressions," NBER Technical Working Papers 0240, National Bureau of Economic Research, Inc.
  12. Lewellen, Jonathan, 2003. "Predicting Returns With Financial Ratios," Working papers 4374-02, Massachusetts Institute of Technology (MIT), Sloan School of Management.
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