The Myth of Long-Horizon Predictability

39 Pages Posted: 29 Mar 2006 Last revised: 10 Nov 2022

See all articles by Jacob Boudoukh

Jacob Boudoukh

Reichman University - Interdisciplinary Center (IDC) Herzliyah

Matthew P. Richardson

Department of Finance, Leonard N. Stern School of Business, New York University

Robert Whitelaw

New York University; National Bureau of Economic Research (NBER)

Multiple version iconThere are 5 versions of this paper

Date Written: December 2005

Abstract

The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.

Suggested Citation

Boudoukh, Jacob and Richardson, Matthew P. and Whitelaw, Robert F., The Myth of Long-Horizon Predictability (December 2005). NBER Working Paper No. w11841, Available at SSRN: https://ssrn.com/abstract=893380

Jacob Boudoukh (Contact Author)

Reichman University - Interdisciplinary Center (IDC) Herzliyah ( email )

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Matthew P. Richardson

Department of Finance, Leonard N. Stern School of Business, New York University ( email )

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Robert F. Whitelaw

New York University ( email )

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National Bureau of Economic Research (NBER)

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