Uncloaking Campbell and Shiller's CAPE: A Comprehensive Guide to its Construction and Use
Posted: 22 Mar 2016 Last revised: 22 May 2019
Date Written: August 15, 2016
Abstract
Professors John Campbell and Robert Shiller’s Cyclically Adjusted Price-Earnings (CAPE) Ratio has proven to be a powerful descriptor, as well as a useful predictor, of long-term equity returns in the United States and some global markets. In recent years, though, it has been criticized for being overly pessimistic about the prospects for equity returns, its lack of robustness to distortions in corporate earnings, and for overstating the predictability of returns at long horizons on account of overlapping observations and endogeneity, particularly when estimated using Ordinary Least Squares (OLS).
In this paper, we explore various definitions of CAPE, present new construction techniques that make it robust to a wide range of accounting and index construction biases as well as to changing fundamentals in equity markets, and evaluate its forecasts over various time periods using econometric methods that account for endogeneity, overlapping observations and the presence of outliers. We show that many of these enhancements have a minimal impact on CAPE and its forecasts for the US equity market, but prove useful in smaller markets and in markets that have experienced significant dislocations. In addition, we show that CAPE’s forecasts of market return can be usefully supplemented, and even enhanced, by the use of accounting flow variables such as cash flow and revenues in place of earnings and cyclically adjusted earnings. Finally, we show that CAPE and its many variants forecast nominal returns more effectively than real returns. We use these techniques to derive a robust estimate of the expected return of equities in the U.S., and show that it is currently on the order of 6% per annum.
Keywords: CAPE, Shiller's CAPE, Campbell and Shiller's CAPE, Shiller P/E, Expected Return, Valuation Ratio, Campbell and Shiller, Hjalmarsson, Scaled t-test, endogeneity, overlapping observations
JEL Classification: C51, C52, C53, G10, G11, G12, G31
Suggested Citation: Suggested Citation
