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Journal ArticleDOI

Market Expectations in the Cross‐Section of Present Values

Bryan T. Kelly, +1 more
- 01 Oct 2013 - 
- Vol. 68, Iss: 5, pp 1721-1756
TLDR
Kelly et al. as mentioned in this paper showed that relying on aggregate quantities drastically understates the degree of value ratios' predictive content for both returns and cash flow growth, and hence understate the volatility of investor expectations.
Abstract
Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross-section of book-tomarket ratios, we find an out-of-sample return forecasting R 2 of 13% at the annual frequency (0.9% monthly). We document similar out-of-sample predictability for returns on value, size, momentum, and industry portfolios. We present a model linking aggregate market expectations to disaggregated valuation ratios in a latent factor system. Spreads in value portfolios’ exposures to economic shocks are key to identifying predictability and are consistent with duration-based theories of the value premium. THE MOST COMMON APPROACH to measuring aggregate return and cash flow expectations is predictive regression. As suggested by the present value relationship between prices, discount rates, and future cash flows, research shows that the aggregate price-dividend ratio is among the most informative predictive variables. Typical in-sample estimates find that about 10% of annual return variation can be accounted for by forecasts based on the aggregate book-tomarket ratio, but find little or no out-of-sample predictive power. 1 In this paper we show that reliance on aggregate quantities drastically understates the degree of value ratios’ predictive content for both returns and cash flow growth, and hence understates the volatility of investor expectations. Our estimates suggest that as much as 13% of the out-of-sample variation in annual market returns (as much as 12% for dividend growth), and somewhat more of the insample variation, can be explained by the cross-section of past disaggregated value ratios. To harness disaggregated information we represent the cross-section of assetspecific book-to-market ratios as a dynamic latent factor model. We relate disaggregated value ratios to aggregate expected market returns and cash flow growth. Our model is based on the idea that the same dynamic state variables driving aggregate expectations also govern the dynamics of the entire panel ∗ Kelly is with Booth School of Business, University of Chicago, and Pruitt is with the Board of Governors of the Federal Reserve System. The view expressed here are those of the authors and do not necessarily reflect the views of the Federal Reserve System or its staff. 1 See Cochrane (2005) and Koijen and Van Nieuwerburgh (2011) for surveys of return and cash flow predictability evidence using the aggregate price-dividend ratio. Similar results obtain from forecasts based on the aggregate book-to-market ratio.

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Citations
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A unified measure of Fed monetary policy shocks

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Bond Risk Premia with Machine Learning

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References
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Halbert White
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Journal ArticleDOI

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TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.
ReportDOI

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Whitney K. Newey, +1 more
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TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
Journal ArticleDOI

Capital asset prices: a theory of market equilibrium under conditions of risk*

TL;DR: In this paper, the authors present a body of positive microeconomic theory dealing with conditions of risk, which can be used to predict the behavior of capital marcets under certain conditions.
Journal ArticleDOI

Risk, Return, and Equilibrium: Empirical Tests

TL;DR: In this article, the relationship between average return and risk for New York Stock Exchange common stocks was tested using a two-parameter portfolio model and models of market equilibrium derived from the two parameter portfolio model.
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